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QUT KCB206 2014 Tutorial Group 7
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RT if you cried
In all honesty, I found that writing this post and this topic in general was pretty difficult. I’m not interested extremely interested in politics and how it effects social media and technology. In saying that though, in week 8 Theresa discussed the different aspects and perspectives of new media politic and engagement. “Social media tools are not a replacement for real-world action but a way to coordinate it.”(Shirky, 2012). As I think I said in my first blog, if you aren’t on social media you’re blocking yourself from a lot of the world. I think it was only a matter of time for politics became a thing on Facebook’s latest trend.
In a social-media crazed society, insignificant measures are seen as influential. A mere "RT" on a Twitter post, "like" on a Facebook status or "tag" on an Instagram photo has become the mechanism to create change. You’ve all seen it on your newsfeed, 1 like = 1 prayer for this picture of a man sitting on the sidewalk, with text claiming he’s homeless and that somehow your likes will help him out. And you see people liking it, why? We all want to make ourselves feel better by “helping out” the lesser. It’s what I like to call fake activism. And the culprits aren’t just your Facebook friends; even on Twitter fake activism runs rampant. Numerous tweets state a message synonymous with "something tragic happened. RT this post or you have no heart”. It’s ridiculous; the logic behind this movement is flawed because a retweet does not prove that somebody really cares about a cause. A like isn’t going to change the world over night. Sure it might make people aware of the situation, but liking a picture isn’t going to fix the problem.
Let’s go back to around 2012, if you were a regular Facebook user then I can guarantee you’ve heard of the infamous Kony 2012 campaign. On March 5, 2012 a 30-minute non-profit-made video brewed an unprecedented level of social media buzz and backlash (Fox. 2013). It literally blew up over night, it seemed as though everyone was talking about it. But was it helpful or successful? I can guarantee that it was successful, not in the stopping this crazy military/kidnapper, but in becoming viral and earning the filmmakers millions, yes it was. Over the last year, the YouTube version of the film has been viewed more than 96 million times. On Vimeo, the film's original host, it has been viewed 18.4 million times. Would it have been as successful if it weren’t on social media? No. I can guarantee there is no way it would’ve gotten the views or interest it had if it had been broadcast on the news. People felt compelled to spend their money on this cause. They annoyed friends with the constant updates and posts about this man. Was it successful? Yes and no. While it did draw attention to this matter, Kony is still out there.
While I’m not in love with this topic, but I definitely have a better understanding of it, now that I’ve looked into it more. It shows the effect social media is having on the world. As I said before there’s no way that something as massively popular as Kony, would’ve been successful if it had just been shown on the news. The world is adapting and evolving and we have to as well if we want to keep up.
Fox, Zoe. 2013. “Kony 2012' One Year Later: Success or Failure?”. Accessed April 17, 2014. http://mashable.com/2013/03/05/kony-2012-retrospective/
Shirky, Clay. 2011 “The Political Power of Social Media: Technology, the Public Sphere, and Political Change.”In Foreign Affairs 90:1. Available at:http://www.foreignaffairs.com/articles/67038/clay-shirky/the-political-power-of-social-media
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WEEK 10 BLOG: NEW MEDIA, BIG DATA & TELEMETRICS
So this week’s topic is focussed around new media, big data and telemetrics. When referring big data to new media, I find it really interesting knowing statistics of social media data and user participation around that field. Twitter is a prime example when researching data analysis due to the openness of information and data sharing. When analysing big data with Twitter, there are approximately 645,750,000 active users tweeting and posting, with 135,000 new twitter users signing up everyday. On average, there are 58 million tweets per day and 9,100 tweets every second, that is a lot!
Something I found interesting in this week’s reading by Eric Siegel was that data embodies a priceless collection of experience from which to learn. Whether it is a Facebook post, Instagram photo or a new Tweet, it is encoded as data. The process of API is used to stream and decode data on Twitter whereby functions and procedures are proposed to allow the creation of applications and access to online data. In referring to Twitter, API’s contain parameters which can include such things as hash tags, keywords, geographic regions and Twitter user ID’s.
When researching new media and big data I thought it would be interesting to bring up the topic of 2014’s ‘best selfie’ taken at the Oscars. Ellen DeGeneres began taking selfies as she walked down the hall, after a few here and there she invited a group of selected celebrities to join in, in attempt for a new breaking Twitter record. This photo was posted to many social media platforms and on Twitter and was re-tweeted over 3,429,171 times. Ellen DeGeneres, the director and publisher of this image multiplied her twitter followers by more than 47 times jumping from 25.3 million followers on the 1st of March to 26.4 million by the next day.
https://www.youtube.com/watch?v=GsSWj51uGnI
It’s amazing to think just one photo can have such an impact over social media. I have found this week’s topic of new media, big data and telemetrics really interesting, I love knowing statistics on a social media platform that I use several times a day. It’s so shocking to see how fast media takes over, it’s hard to catch up with all the new technology being developed to process new media. But at the same time, this new era of technology will only improve for the better and I’m looking forward to what the future of social media will be in 10 or 20 years time to come. Thanks for listening.
REFERENCES
Harrington, Stephen. 2013. “Ch 18 Tweeting about the Telly: Live TV, Audiences, and Social Media.” In Twitter and Society edited by Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt & Cornelius Puschmann, 237-248. New York, NY: Peter Lang.
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analytics, 1-16. Hoboken, NJ: John Wiley and Sons Inc. (Available on CMD)
https://blog.twitter.com/2014/looking-back-at-the-2014-oscars-on-twitter
http://www.statisticbrain.com/twitter-statistics/
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Predicting The Future With The Past
Darryl Woodford presented this week’s topic New Media, Big Data and Telemetrics. It was very interesting, as I had not looked into data before. It made me realise just how much information is out there and how much of it is mine. It reminded me a lot of an exercise we did in the first few weeks of tutes where we wrote down all the social media interfaces and online accounts that we had. I think we came up with at least 25 that a majority of people had opened since being active online. Whether or not you use all the accounts the data is still out there somewhere, which is a scary thought.
I was really interested in the idea of telemetrics and utilising to find out where your audience is. It really relates to my career in the film industry and how I can incorporate it into transmedia marketing for my third year films and into the future (Woodford, 2014).
In Seigels paper, The Prediction Effect, he explores what is predicable with data collected though internet statistics. The answer is pretty much anything you want! Some examples I found interesting were: Energex predicting the energy demand, personalized shopping coupons by UK supermarket giant Tesco and those super awkward online dating sites (Seigel, 2013). I've always known through eHarmony ads that they use some form of compatibility scheme to match people with their "soul mate" but it never occurred to me that they would actually use“real" data to make these matches. They actually have a copyright name for their data prediction programme: eHarmony Compatibility Matching System™(eHarmony, 2014).
An interesting point that Seigel also raises is that predication of the weather, which had been around for years, well before the Internet is only 50% accurate. Predicting data relating to humans is much less accurate. However we can eliminate these inaccuracies and risks by directing the data to the right people through marketing. The two go hand in hand with each other.
Because this is my last blog for Internet Self and Beyond (and probably forever) I guess I should sum up a little of what I've learned but Im just going to leave you all with my favourite viral goat video because what I've learned in this subject is that anything can happen on the internet and that everyone needs more goats in their lives :) Till next time!
https://www.youtube.com/watch?v=5IuRzJRrRpQ
Woodford, Darryl. 2014. “KCB206 Internet, Self and Beyond: New Media, Big Data and Telemetrics.” Accessed May 12, 2014. http://blackboard.qut.edu.au/webapps/portal/frameset.jsp?tab_tab_group_id=_4_1&url=%2Fwebapps%2Fblackboard%2Fcontent%2FlistContent.jsp%3Fcourse_id%3D_108110_1%26content_id%3D_5232451_1
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analytics, 1-16. Hoboken, NJ: John Wiley and Sons Inc
eHarmony Australia. 2014. “Company History". Accessed May 1, 2014. http://www.eharmony.com.au/about/eharmony/
http://cdn.memegenerator.net/instances/400x/25719819.jpg
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New Media and Politics
Judy Lewis | 04.04.14
New media and politics is something that I had never had much interest in. I used to follow ex Prime Minister, Kevin Rudd on Instagram and Twitter as a bit of a joke. It was like having your mate’s dad on social media, he was a fun guy and it was amusing to watch an older person using these websites. Nevertheless, after the novelty had worn off I proceeded to unfollow him on both accounts. Looking back at the situation now I realize that while I had been liking his posts and having a laugh at the excessive use of emoticons, I had become more inclined to like him as a person and in turn as a politician.
Given that this was a time somewhere between his downfall and rise back to power, I realize that I had started to sympathize with him in a way that could never have occurred without the use of social media. My thought process went something a long the lines of: Look at my poor buddy, KRudd on Instagram, his poor ‘friends’ have stabbed him in the back yet look at him being a true Aussie and carrying on with his life, enjoying each and every day. I found that a lot of my friends felt similar sentiments, often sharing his posts and tagging their friends in the comments section. It was only after unfollowing him that I became immune to this way of thinking. Yes, he might be a nice guy but is he able to govern our country? Took over my original concerns of how appatezing his blue icing and chocsprinkles cupcakes looked.
This is an example of what Theresa mentioned in the lecture about politicians not only campaigning through speeches and fundraisers but by using social media, to subtly manipulate voters (Sauter, 2014). An even better example of this is of course Obama’s campaign where many claim that the successful use of social media won him the position as president of the US. On the other side of the spectrum of course, is governments using social media technologies to suppress its citizens through monitoring and restricting access to social tools.
Secretary of State, Hilary Clinton announced funding for the development of tools designed specifically for reopening access to sites such as Google, YouTube and the New York Times to countries that have restrictions upon them (Shirkey, 2011). However in these countries what good is access to Western information if the people have no means of networking and communicating. There are so many different angles to the situation.
Information acts as a nail, and social media acts as a hammer. The two are useless without the other and even then no actual change can be made to the surface unless a person commits to an action, picks up both and hammers away.
Click to follow KRudd on Instagram and on Twitter!
References:
Sauter, Theresa. 2014. “KCB206 Internet, Self and Beyond: week 8 lecture notes.” Accessed April 26, 2014. http://blackboard.qut.edu.au/bbcswebdav/pid-5284591-dt-content-rid-2294437_1/xid-2294437_1
Shirkey, Clay. 2011. “The Political Power of Social Media:
Technology, the Public Sphere, and Political Change”. Accessed April 26, 2014. http://www.foreignaffairs.com/articles/67038/clay-shirky/the-political-power-of-social-media
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Legal Issues
Judy Lewis | 20.04.14
This week was a topic that I assumed I would find dull, instead I found myself being rather interested in the ongoing question of does Internet law actually exist? Of course it does, was my immediate reaction as numerous examples popped into my head. Why else would those residing in China not be able to access Facebook, why else would Julian Assange be on the run for information he revealed on the Internet? I soon began to realize that these were just further examples of Judge Frank Easterbrook’s “Law of the Horse” (Flew. 2014. P. 180). China does not have an Internet law, but rather laws that involve its residents using the Internet.
Further into the discussion I become more interested in the topic of if someone were to govern the Internet who would I, as an everyday user want that to be? Should no one govern the Internet? Or should it be in the hands of a corporation or a national or a transnational government? At the end of the day, everyone has an agenda. Even if it were myself who were to govern the Internet, my main concern would be for me, ensuring privacy for myself but having access to anything that I deemed appropriate. Of course the personal online privacy of Judy Lewis and whether she can access any file and website is perhaps not the top priority for most organizations or governments.
When contemplating who should have control over the Internet, it’s important to note what exactly they’ll be faced with such as; the intangibility of digital information, global internet and national laws and the continually changing nature of digital media forums (Flew, 2014). The three challenges discussed in the previous week are so overwhelming that I’m unable to come up with answers, just more questions.
It is reassuring to see in Flew’s Journal, that somewhere in Australia, people more informed on the matter than I am, are taking progressive steps to answering these questions, however undefined their answers may be. The ALRC (Australian Law Reform Commission) in their latest report have focused specifically on the matters of ‘fair use’, taking a position of referee in a sport where a lot of the foul play goes unnoticed, the rules are forever-changing and the calls are mostly decided through judgment (Flew,2014, p. 41). Perhaps not the most absolute solution but hey at least I, as an everyday Internet user residing in Australia can access Facebook.
References:
Flew, Terry. 2014. “KCB206 Internet, Self and Beyond: week 7 lecture notes.” Accessed April 13, 2014. http://blackboard.qut.edu.au/bbcswebdav/pid-5284591-dt-content-rid-2294437_1/xid-2294437_1
Flew, Terry. 2014. New Media. South Melbourne: Oxford University Press
Flew, Terry. 2014. “Fair Use and the Future of Copyright.” Internet Law Bulletin 17. (2): 41-43.
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Mediated Communication
Judy Lewis | 13.04.14
The topic for this week is one that I had never given much though to before. Never having experienced a time before mobile phones and home computers, the ability to interact with anyone I wanted at the touch of a button was of little awe to me as it was just always present.
The process of ‘domestication’ is where a new device becomes a normal component of everyday living. (Baron, 2008, p. 3). An example provided by Naomi Baron that I found particularly interesting is the process of flying; when it was still a novelty people would dress well specifically for the occasion, whereas now dress codes range anywhere from trip to the grocery store to important business meeting.
Reflecting on my own personal situation, it wasn’t so much that new media technological advances weren’t a big deal, its just that they always there. Myself and the many other first world children that I grew up with were growing at the same time that this technology was. Instant messaging and social media was the next step from emails and telephone calls, it was as natural as going from primary school to high school, no questions asked, this is how it’s supposed to happen.
Now however, when I reflect on the number of younger children on Facebook, I feel as though they’ve skipped eight or ten steps: no first you have to get email, and then you have to get msn instant messenger, and then you get MySpace, and then maybe you can experiment with Bebo, and then and only then can you get a Facebook, it’s just the natural path of life. Of course what I’m feeling is nothing new to what has been felt before, first you have to handwrite your letters, then you can telephone on a landline, then and only then can you maybe buy a home computer or cellular phone.
Another aspect that amused me was the concept that caller ID has become the new form of crossing a street to avoid an unwanted conversation. The image of an old family friend pop up on your phone screen is similar to the feeling of them begin to recognize you on the street, as the ringing continues it replaces the quickened pace as they begin to approach you, and as you select ignore and turn your phone over, the act replaces crossing the street. However unlike in real life, if the unwelcome party were to continue their pursue by crossing the road with you, if they were to continue ringing, a simple action of blocking the pursuer would be the equivalent of having the person disappear completely all together. Though many might be thankful for this ability, the act really brings up the concerning view of how far new media technologies allow us to completely shut people out of our lives.
References:
Naomi Baron. 2008. Always on: Language in and online and mobile world. Oxford: Oxford University Press.
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Produser
Judy Lewis | 06.04.2014
For the past few weeks we’ve discussed the blurring of the lines between consumer and prodcuer to create the ‘produser’. Similar to last week’s blog, a reoccurring theme has arisen, that being the idea that one person’s idea of creative collaboration can actually lead to a certain level of exploitation between the consumer and the producer. An obvious platform for this is YouTube. Is there really such a thing as equality between consumer and producer on such a free for all medium? A medium where the rules and guidelines for fair play are hidden amongst pages of size 8 font titled Terms and Agreements.
A dominant theme amongst critics of Web2.0 is that user-generated content involves unpaid for work, a form of ‘free labour’ from participants. The notion that you will put in your time, effort and resources like any other 9-5 job but at the end of the day you will be left with nothing. Particularly for projects such as the on we saw in last week’s lecture, where a conductor asked for video submission of individuals singing and then combined all 100+ submissions to create a “virtual choir” (Sauter, 2014). Though a beautiful piece and an insight into what the web can do for us, behind it all is the dilemma of who takes the credit.
Another examples of this is the Glee tribute episode where the cast of the hit television show paid their respects to the late Cory Montieth. Used in the opening credits of the show was a new logo used specifically fro the episode with the silhouette of Montieth’s character, Finn Hudson waving.
This logo was earlier tweeted several months before by the producer Ryan Murphy with the caption, “A talented fan made this and I thought it was really moving.” (Douglas, 2013).The tweet has since been deleted and the source remains unknown still but was used as the logo for the show, so has Murphy taken advantage of and exploited this fans photoshop skills? On the other side of the spectrum, the fan has used and altered an existing and copyrighted logo so it could be argued that the fan has breached the legal copyright right of the show. I’m not particularly condemning either side, it was a touching logo that I’m sure many fans appreciated, but again, who takes the credit?
The consumer and Producer relationship is a complicated one that stands on, and very frequently crosses the line between what some would refer to as exploitation. However, what some may claim as exploitation is seen by many others as a form of creative collaboration that benefits so many more than it actually harms
To follow Ryan Murphy on Twitter follow this link
References
Burgess, Jean and Joshua Green. 2009. YouTube: Digital Media and Society Series. Cambridge: Polity Press.
Douglas, Beth. 2013. “Cory Monteith’s Death: Ryan Murphy Shares ‘Moving’ Fan Tribute Art.” Accessed March 30, 2014. http://www.wetpaint.com/glee/articles/2013-07-30-cory-monteiths-death-ryan-murphy
Sauter, Theresa. 2014. “KCB206 Internet, Self and Beyond: week 5 lecture notes.” Accessed March 30, 2014. http://blackboard.qut.edu.au/bbcswebdav/pid-5284591-dt-content-rid-2294437_1/xid-2294437_1
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Crowdsourcing
Judy Lewis | 30.03.14
Crowdsourcing was the main topic of this week’s lecture and is another example of how new media blurs the lines, in this case the lines between consumption and production (Sauter, 2014). For many people crowdsourcing is an opportunity for community participation in a way that has never before been possible. However, others like Christian Fuchs take a more cynical approach, claiming that social media is not by any means a public sphere or a democratic space but rather dominated by multimedia organizations and anyone who disagrees is deluding themselves with an ideology that isn’t a reality (Fuchs, 2014, p. 102).
Fuchs makes the point that when crowdsourcing, websites such as Google have little to no interest for the benefits of the everyday user but rather to reduce their own costs by exploiting these people (Fuchs, 2014, p. 102). In reading this, the idea being conjured in my head is of a first world sweatshop, unlike the sweatshops in India however, the workers sit on their MacBook Pro’s in their well furnished homes with their fully stocked fridges.
As evident in these two pictures, there’s a vast difference in terms of lifestyles. One who is forced into working for long hours and low wages and another who chooses to take part in an activity and has the free will to stop whenever they want. In my opinion the term ‘exploitation’ in this scenario is being overused, when put into perspective the everyday Internet user has the ability to choose what to do with their time, business such as Google have acknowledged this and done so to their advantage. Of course an argument could be made that they are also taking advantage of the user, but not in the same way that Nike does with its sweatshops.
When looking at the bigger picture crowdsourcing provides as many benefits for the consumer as it does for the producer. Unlike Fuchs believes, the Internet isn’t all about the big organizations, with these new media formats and tools, new relationships have been established that could never have existed before, relationships that allow the everyday user to have a voice rather than just ears.
References
Alexander Wimmer. “The importance of an online presence.” Accessed March 27, 2014. http://blogs.ubc.ca/alexanderwimmer/2013/11/30/the-importance-of-an-online-presence/
Fuchs, Christian. 2013. Social Media: A Critical Introduction. London: Sage Publications.
Sauter, Theresa. 2014. “KCB206 Internet, Self and Beyond: week 4 lecture notes.” Accessed March 27, 2014. http://blackboard.qut.edu.au/bbcswebdav/pid-5284591-dt-content-rid-2294437_1/xid-2294437_1
Tamari Ramishvili. "Sweatshops and child labor: The price of fashion?" Accessed March 27, 2014. http://gleaner.rutgers.edu/2012/04/sweatshops-and-child-labor-the-price-of-fashion/
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Big Data = Big Deal
This week in KCB206, we explored new media, big data and telemetrics. My initial impression of the topic was, ‘Oh, that sounds boring’, then after Darryl Woodford’s presentation and the related videos, my feeling towards the topic quickly turned to fear.
I always thought it was a bit unnerving that the Maps app on my iPhone knows ‘the direction to home’. Now, I know how it knows, and it is scary.
Every action made online, whether it’s a post, a search, a tag, a purchase, a new account, or anything you click, every bit is a piece of digital information that is documented and sent off into the infinite realm of big data. This data is then put in the hands of researchers, who compile this information for commercial companies and governments to gain knowledge of you, the user, in order to alter and personalise the online experience to suit your interests.
Yeah, scary.
But Eric Siegel assures us in his reading that ‘data embodies a priceless collection of experience from which to learn’ (2013, 3), so despite its scariness, it is a valuable source of digital information and can also lead to potential opportunities for improved technologies, especially predictive technology. To which Siegel further highlights, ‘the process of machines learning from data unleashes the power of this exploding resource. It uncovers what drives people and the actions they take-what makes us tick and how the world works. With the new knowledge gained, prediction is possible’ (2013, 4). The ability to predict human response and behaviours towards certain circumstances would be beneficial for these companies and for everyday people alike.
However, at the same time Siegel acknowledges that prediction is not and never will provide definite answers. He states, ‘the future is unknown, and uncertainty is the only thing about which we're certain’ (2013, 10). But that’s okay, apparently, as predictions do not need to be completely accurate in order to produce valuable information.
Siegel’s reading changed my feelings towards big data to be hopeful for the opportunities that it may produce. But that was quickly changed after I did a quick search of the Internet and found that big data is a subject heavily studied by numerous researchers from an array of academic fields. A particular video took me back to the fearful and nervous disposition. Alessandro Acquisti addressed the serious privacy issues that are at the centre of the big data studies. He asserts, ‘we do reveal so much more information about ourselves online than ever before, and so much information about us is being collected by organizations. Now there is much to gain and benefit from this massive analysis of personal information, or big data, but there are also complex trade offs that come from giving away our privacy.’ (2013)
The full video:
These and many more videos posted online disclose the potential benefits and limitations of big data research. Overall though, I’m still a bit anxious. The data that is being collected about me may be for good reason, and may even be beneficial to me. Yet, the idea that all of my online activity is documented and tracked and saved for reasons that are unknown to me, needless to say, makes me a little uneasy.
References
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analytics, 1-16. Hoboken, NJ: John Wiley and Sons Inc.
Woodford, Darryl. 2014. KCB206 Lecture: New Media, Big Data and Telemetrics. Accessed May 11, 2014. http://www.dpwoodford.net/wp-content/uploads/2014/02/KCB206-Big-Data-Lecture_Small.pdf
Woodford, Darryl, Katie Prowd and Axel Bruns. (forthcoming). “Telemetrics: Towards Measuring Social Media Engagement with Television.”
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Big Data
The Internet’s “footprint” has drastically increased since it first became accessible to consumers in the late 1980s. By mid 2012 it had reached over 2.4 billion people around the world. When we use the Internet we leave traces of ourselves. Every link we click, photo we share and every video we watch create information about ourselves. So what is Big Data? It’s a way to use what you can relate to your customers, you want to know how what you know can be used to make your relationship with your customer better (Wareham. 2014). For most producers of any business that means Big Data needs to drive your understanding of your customer.
To be honest when reading about this topic I did find myself procrastinating, I did not think that a topic like Big Data could possibly interest me. I was proved wrong. Now while I wouldn’t go out and enrol myself into an online marketing course, I can safely say I am quite fascinated with the whole idea of using an audience’s digital footprint to advertise your business.
Have you ever used a computer to browse a clothing website or Googled your favourite movies and a few hours later an ad pops up on Facebook relating exactly to what you were looking at? That’s big data; the Internet is filtering through the various websites you are using to give you information relating directly to you. Basically the real value of this data comes from the conclusions we draw, not the raw materials we access (Siegel. 2013). A great example of this is the What’s Trending tab on Facebook, the most popular tags on Tumblr and the trending hash tags on Twitter. It’s a way to see what people are discussing, what’s popular right now. It’s a great way to cater to your audience’s wants and needs. If something were the trending topic on Twitter, any smart business would take that opportunity to reach out to this audience, or use social media to get themselves trending. If you’re in the field of online marketing or content marketing and want to ensure that you’re bringing the best data to bear on your projects.
Even now, I’ll scroll through my news feed on Facebook and without a doubt I can guarantee that if I even think about buying something, I’ll get an ad suggesting I buy something from the same brand. You can’t escape it, it’s everywhere, and while sometimes it can be a bit overbearing, if used right it could be a great business tool. You are constantly putting yourself in the face of millions of people, who are constantly, like me, scrolling through Facebook or Google.
So even though words like data and analysing might frighten me a bit, I think I can safely say that while it may not completely appeal to me, I have a greater understanding and appreciation for this topic. Definitely something that, being in the film business, could come in handy one day.
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analysis, 1 – 16. Hoboken: John Wiley and Sons Inc.
Wareham, Chris. 2014. “Why big data is different from customer analytics”. Accessed May 11, 2014. http://blogs.adobe.com/digitalmarketing/analytics/big-data-different-customer-analytics/
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WEEK 10 BLOG: Big Data and My Issue with Entertainment
Week 9 was on the topic of Big Data. A concept, which to be honest I do not like. Big Data is comprised of every electronic move you make whether that is clicking on a website, online shopping, watching videos, enabling GPS in your phone etc. All of these actions create data that is recorded via the cloud - data which is sent to oversize computers whose sole purpose is to collect and store this information. What businesses and governments do with this data not legislated - they can do whatever they wish - and i think this is what scares me.
While many different positive outcomes are likely to arrise from the use of big data - examples can be seen here or here. One of these examples was spoken about in Jenna’s 5 minute review at the beginning of the week - The Gates Foundation and the Polio Program (here is a link to her blog post this week)
I am nervous about the ways in which Big Data could be abused by those in power - both in government and in business. Google is currently the main collector of Big Data with Google Ads displaying items that you may have searched for or added to an online shopping cart. To me it seems like an breach of trust and privacy - it seems eerie and off-putting to see an item in my shopping cart advertised to me while i am searching for information to compete uni assignments (not to mention distracting).
What negative impacts could come from big data?
Unstable governments could use big data as a way to track and target individual citizens who do not agree with their regime. It could be used to enforce a totalitarian state. We have already seen examples of this sort of story - and i will keep my eye on the recent news story about Iranian Women Ditching Head Scarfs and the display of this on Facebook. It would not surprise me if Government Intervened.
Finally, while others have spoken about the positives of Big Data in the Heath Industry I have concerns in regards to these comments:
While being able to decode human DNA at an affordable price would bring around cures to certain diseases and illnesses, this ability could enable a Gattaca-esque society to form, with DNA decoded at birth to find illness leading to discrimination. If you haven't seen the movie Gattaca from 1997, i recommend you do, as it is one of my favourites and has a strong storyline that revolves around Decoding DNA and the discrimination that would ensue. A trailer is included below.
Overall throughout the semester we have covered many different topics within the new media environment. I have learnt a lot about each topic - including that i consume far too much futuristic, dystopian entertainment. I have also discovered that if i want to have a positive opinion on the topics discussed, i should probably step away from both Orwell and my favourite movies. What has everyone else thought about entertainment and the topics, have books or movies given you a strong opinion on the topics? Or have you been able to separate Fiction from the future of New Media?
References:
Woodford, Darryl. 2014. “New Media, Big Data and Telemetrics.” QUT Lecture , echo file posted May 1. Accessed May 10, 2014. https://lecturecapture.qut.edu.au/ess/echo/presentation/11dcf106-e7c9-44eb-a753-74dfff689043?ec=true
Youtube. “What is Big Data.” 2012. Accessed May 10, 2014. https://www.youtube.com/watch?v=ahZGEusG13A
Youtube. “What Big Data Says About You.” 2013. Accessed May 10, 2014. https://www.youtube.com/watch?v=fc1zBNC9wNY
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Biggg DATA and Businesses
As we come to the final blog, Darryl covered the topic of New Media, Big Data and Telemetrics. Honestly, I had no idea what this topic was about or how it would relate to us. However, from Darryl’s lecture and the weekly readings, along with this video, http://www.youtube.com/watch?v=TzxmjbL-i4Y, I now understand ‘big data’ and how the data allows opportunities for a better business/company.
Every day, people are constantly clicking, searching and switching on and off that are continually being collected, which forms into what we call ‘data.’ As Siegel mentions data is a ‘priceless collection of experience from which to learn.’ (Siegel, 2013) The data collected is also consistently growing and expanding to an estimate of 2.5 quintillion bytes per day. (Siegel, 2013) Initially, the data collected of what has been clicked or switched can eventually be used to predict people and the trends, as Siegel states ‘with the new knowledge gained, prediction is possible.’ (Siegel, 2013) While, prediction comes from the data it allows businesses to utilize the data in an effective manner. Additionally, I found it interesting how Don Tapscott in the ‘What is big data?’ video addressed the idea of how data allows the ability for ‘businesses to push information to the customers more effectively.’ (Economist, 2012) The data that are used to predict and outline trends, primarily allows businesses to boost sales from the data received as they anticipate and adapt to shift customers desires and to reach customers with targeted advertising.
An example where big data is used effectively to enhance businesses is a Hong Kong watch company, O.D.M Design and Marketing. They noticed that their sales data from the Tmall.com store, one of China’s top online shopping websites, was revealing an interesting trend. (Lee, 2014) A particular bright silicone-strapped watch had rapidly become popular with young people in china. The sales data allowed them to quickly launch marketing campaigns that targeted these Chinese students. Businesses will therefore be capable to capture a better understanding of which product is in trend and who the product is more appealed to from the data. Alternatively, data is also effectively used for television. According to an article I was reading, Time Warner Cable uses big data tools to navigate the changing media landscape. (Big Data Startup, n.d.)The data information they receive allows them to alter their infrastructure that suits the needs of their customers. Audience metrics provided from the data, provides the capability of knowing what their customers are looking for. Eventually, this could lead to a new revenue streams for Time Warner Cable, which will fulfil the customers’ needs. ‘Big data’ can ultimately ‘shape the fortunes of companies capable of examining, interpreting and acting upon the messages that mountains of information have to tell.’ (Lee, 2014)
I believe that the use of data with predictions and trends, will in fact improve businesses. ‘Data’ will improve businesses and fulfil customers as businesses will be able to analyse information and adjust to reflect the customers’ information and initially what you have previously clicked on. However, with data expanding every day this may mean collected prediction and trend information isn’t completely accurate. So, do you think businesses are improving from the data information provided?
REFERENCE
Big Data Startup. N.d. “Time Warner Cable.” Accessed May 10, 2014. http://www.bigdata-startups.com/BigData-startup/time-warner-cable-big-data-optimize-viewers-experience/
Economist. 2012. “What is Big Data?” Youtube video, posted June 26. Accessed May 7, 2014. https://www.youtube.com/watch?v=ahZGEusG13A
Funk-e Studios. 2013. “What is Big Data and How Does it Work?” YouTube video, posted November 12. Accessed May 9, 2014. http://www.youtube.com/watch?v=TzxmjbL-i4Y
Lee, Melanie. 2014. “Tmall.com’s Big Data Push Reaps Rewards for Virtual Stores.” Yahoo, March 11. Accessed May 9, 2014. https://smallbusiness.yahoo.com/advisor/tmall-com-39-big-data-push-reaps-rewards-063722381.html
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analysis, 1 – 16. Hoboken: John Wiley and Sons Inc.
Woodford, Darryl. 2014. “New Media, Big Data and Telemetrics.” QUT Lecture , echo file posted May 1. Accessed May 5, 2014. https://lecturecapture.qut.edu.au/ess/echo/presentation/11dcf106-e7c9-44eb-a753-74dfff689043?ec=true
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Big Brother & Big Data!
Like most of the young tech savvy media and communications students at my university, I am an avid user of social media platforms. Communicating to friends, family and the people I follow with a naïve disregard for the digital profile I am creating with every click. Data is possibly one the most valuable resources in the digital world. Harvested by your every web interaction and analysed by commercial giants in order to deliver commercial content with precision. Welcome to the world of big data, where big brother knows you better than your own mother!
(How big data is changing the world - Online news corporation)
The concept behind collecting data is simple; create a sociological profile from an individual’s online behavior in order to predict that individual’s future behavior. Eric Siegel the author of predictive analysis: the power to predict who will click, buy, lie and die explains that the value is not in the data alone, it is in ‘machined learning,’ computer generated statistical inference that enables accurate predictions to be made from data collected (Siegel, 2013). Therefore personal data is harvested, computer analysed and profiled in a way so that, consumer behavior, democratic behavior and personal behavior can be predicted through our online habits.
As an advertising and media and communication student this kind of information is vital for the future of advertising. Expensive and ineffective models of marketing such as ‘pay and spray’ will become extinct and interactive ‘push and pull’ models will become more prevalent due to the accuracy firms will have with large databases.
At the moment I currently work for a marketing software company that uses survey technology in order to harvest consumer databases for other businesses. It works by distributing surveys through social media platforms and eDM’s with an incentive attached to entice respondents and increase viral sharing. Once a consumer completes the survey and enters the competition, the response and the contact particulars of the respondent are collected and profiled, allowing the business to complete an individualistic and precise re-marketing campaign. The company I work for did not exist when I started my degree and the future of database profiling is sure to become more dynamic over time.
https://www.youtube.com/watch?v=raJOkguPrH4
(The Dark Side Of Big Data - The Economist)
However with a bright future for advertising and marketing companies, data collection paints a bleak picture for digital privacy. The Economist posted a video titled The darkside of big data, which states that “the average privacy policy takes ten minutes to read” and “that 72% of privacy policies allow access to third parties to track internet activity” (Economist, 20120. Therefore the next time you accept a privacy policy or terms and conditions it might be wise to find out what your are really agreeing too, otherwise you may become the next predictable marketing target.
References:
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analysis, 1 – 16. Hoboken: John Wiley and Sons Inc.
The Economist, 2012. The dark side of big data. Accessed on May 11, 2014 via https://www.youtube.com/watch?v=raJOkguPrH4
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Big Data and Telemetrics: Exploring the Unknown
http://londoncalling.co/2014/01/uk-retailer-waitrose-takes-a-different-approach-to-in-store-loyalty-cards-big-data/
Okay, all jokes aside, it is a bit amazing and even scary that big data can be used to create such a staggering response in the real world.
Think about every app you use, every camera you walk or drive past, every tweet you send, every status update you post, every switch you flick on or off, every button you press. The data that every one of these interactions produces quantifies you; tells the story of where you’ve been, what you’ve been watching, how you work out, what you buy and much more, and this happens constantly. Every day this data is propelled into the world and into the hands of researchers, companies, governments and for some of it any interested member of the public.
So what happens with this data?
Woodford (2014) depicts a topical and insightful example of how this data reflects human behavior. Via Twitter, instead of just observing the number of people watching a television show, they go so far as to measure an ‘excitement factor’, which gauges audience engagement with a show throughout its season. They use big data to elaborate on the measurements of human behavior. I’m sure you are all, as I am, just thinking about the innumerable applications for this sort of research.
In the reading by Harrington (2013) he brought up the idea of a ‘virtual lounge-room’ where our interaction with social media, while consuming media through the television, mimics that of our interaction with other people in the lounge-room when we are watching a show. This behavior suggests that, contrary to popular belief, watching tv is often a social practice.
These insights that big data and telemetrics afford are changing the understanding of human behavior and mean that researchers are on the precipice of new breakthroughs across so many fields.
With the use of big data comes ethical dilemma though. Once again we are faced with an evolution in technology that ethical guidelines and legislation cannot keep pace with. A fine balance between ensuring privacy and maintaining freedom and democracy must be struck; though it is difficult to decide where to draw the line between protection and oligarchy.
When power is held by the few, issues surrounding their prerogatives for big data arise. As corporations and governments utilize the data that we make, it begs the question: do the benefits for humanity they discover outweigh the breach of privacy and opportunistic behavior they may foster?
However they are used and to whatever value, big data and telemetrics are set to boom in the next few years and we are ever-fuelling them. It will be interesting to see, both the discoveries that they afford, and how regulation tries to salvage the seemingly distant concept of privacy.
References:
Harrington, Stephen. 2013. “Tweeting about the Telly: Live TV, Audiences, and Social Media.” In Twitter and Society edited by Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt & Cornelius Puschmann, 237-248. New York, NY: Peter Lang.
Woodford, Darryl. 2014. “KCB206 Internet, Self and Beyond: New Media, Big Data and Telemetrics.” Accessed May 1, 2014. http://blackboard.qut.edu.au/webapps/portal/frameset.jsp?tab_tab_group_id=_4_1&url=%2Fwebapps%2Fblackboard%2Fcontent%2FlistContent.jsp%3Fcourse_id%3D_108110_1%26content_id%3D_5232451_1
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"Network of Intelligence and Collaboration"
This final blog post will be on the Week 9 topic New Media, Big Data and Telemetrics by Darryl Woodford (2014). In this blog post I’ll review what big data is and provide an example on how big data is used currently and how important and powerful a tool it is in our modern times. Every time we click on a website or make a purchase we are generating a piece of data. As Siegel (2013) suggests, that data is a priceless collection of experience from which to learn from. Big data is collating that information and understanding customers more confidently and accurately on a much larger scale. According to SAS (2014), the mainstream definition of big data includes the three V’s: volume (the amount of data being collected), velocity (the speed at which data travels) and variety (which includes data in all types of formats). But one particular online visual that stood out to me was this notion, and almost likening Big Data to the planet developing a nervous system – meaning that Big Data has the ability to measure, analyse, visualise and then respond to what’s happening all around the world in real time. I’ve learnt that big data has many universal meanings, and the YouTube video on blackboard ”What is big data?” really outlines what big data means to a business professional in today’s society. Some definitions included: a means to running a better business for customers, providing global access to all the possible information about human response and human innovation, and providing a more accurate analysis that can lead to confident decision making and reduced risks. While I was browsing the web I came across a YouTube video “What Big Data Says About You,” where photographer and journalist Rick Smolan talks about Big Data and mentions an interesting example. In his interview, Rick talks about the Gates Foundation who has being trying to eradicate polio in Nigeria. Looking at satellite maps they found that there were villages in Nigeria that nobody knew existed (they didn’t exist on any known map). So, the Gates Foundation gave out ten thousand GPS enabled cell phones to polio inoculation workers to make sure they go to every single hut (and visit every single family and child). Unless you inoculate everybody you can’t eradicate it, so this idea of using satellites combined with cell phones to eradicate polio is an example of how big data can be used to help people (especially in developing countries). I guess it’s not something that leaps to mind when you talk about big data, but this human story really helped me understand big data in a different way (a way that most of the definitions provided didn’t). In closing, Darryl (2014) covered New Media, Big Data and Telemetrics in the week 9 lecture in depth. Most importantly, it was reiterated that big data is perhaps one of the most important frameworks of our generation. No longer are we an information age but a network of intelligence and collaboration. References Seigel, Eric. 2013 “Introduction- The Prediction Effect.” In Predictive Analytics, 1-16. Hobroken, NJ: John Wiley and Sons Inc. Accessed May 10, 2014. Statistical analysis system (SAS). 2014. “Big Data – What it is and why it matters.” Accessed May 10, 2014. http://www.sas.com/en_us/insights/big-data/what-is-big-data.html Woodford, Darryl. 2014 “New Media: Big Data and Telemetrics: Week 9 lecture notes.” Accessed May 10, 2014. Youtube. “Polio’s Last Percent – Bill & Melinda Gates Foundation.” Accessed May 7, 2014. http://www.youtube.com/watch?v=kU3Lw7Nn3qg Youtube. “What is Big Data.” 2012. Accessed May 7, 2014. https://www.youtube.com/watch?v=ahZGEusG13A Youtube. “What Big Data Says About You.” 2013. Accessed May 7, 2014. https://www.youtube.com/watch?v=fc1zBNC9wNY
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Big Data and Digital Methods
Judy Lewis | 11.03.14
Nothing groundbreaking had been shared with me this lecture. Of course a machine, based on actions, reads data and from it predictions are made (Siegel, 2013, p. 2). I suppose I was never fully aware to the exact extent. I knew that if I ‘liked’ a certain page on Facebook, companies would be able to target their products to me specifically. What I was not aware of was that this applied to just about every single action that I made concerning a social media device.
What struck me to be the most interesting though is Twitter, and how the use of Twitter can be used to identify not only what episodes of TV shows gain the most interest, but at what specific event and by which specific characters. As a fan of HBO’s Game of Thrones, I decided to investigate further into how the show’s Twitter audience can predict the level of interest for the show and its characters.
This is particularly interesting when the idea arises that producers, without directly interacting with the audiences, obtain a decent understanding of what the audience wants. Over the past week, there had been quite a bit of online discussion after David Benioff, one of the shows leading producers made the comment to Entertainment Weekly, "… we were going to stop looking at stuff online because you can go into the rabbit hole and get lost in this world of online Thrones commentary if you're not careful..." (Hibberd, 2014). Following this comment, Internet users escalated into an argument about how the show runners could ever begin to properly meet the expectations of viewers if they were going to close their eyes and ears to avid show watchers (Grayson, 2014).
Though I trusted the producers, as they had not let me down thus far, I did have some fears that they would turn into the next George Lucas of Television. However I, and it appears many others have underestimated the use of Twitter as a means of collecting data. Just by looking at the data obtained from twitter conversations, the producers have the audiences in the palm of their hand. They are well aware of which scenes attract the most interest and which characters to keep, or kill off, due to their popularity.
This begs the question though; can data analytics really replace that of human conversation and interaction? Would it be better, if David Benioff had had that argument over an online discussion board with DragonQueen42? Rather than simply relying on twitter generated data. In my opinion, no. What one passionate audience member and online user says does not in any way reflect the masses of people who watch this successful show, predictive analytics may be far from perfect but it is the best method for giving at least the majority of audiences what they want.
References:
Bennett, Shea. 2014. “How Big Was The Game Of Thrones Season 4 Premier On Twitter And Facebook?” accessed May 11, 2014. http://www.mediabistro.com/alltwitter/game-of-thrones-twitter-facebook_b56311
Grayson, Nathan. 2014. “Game of Thrones' Producers Aren't Listening To You, And That's A Problem”. Accessed May 10, 2014. http://tmi.kotaku.com/game-of-thrones-producers-arent-listening-to-you-and-t-1573170009
Hibberd, James. 2014. “Why 'Game of Thrones' producers ignore the Internet: 'It completely confounds the normal creative process'. Accessed May 10, 2014. http://insidetv.ew.com/2014/05/04/game-of-thrones-ignore-internet/
Siegel, Eric. 2013. Predictive Analytics: the power to predict who will click, buy, lie or die. New Jersey: Wiley
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Big Data- Saving the world one bit at a time
What is big data? How does it learn from us? WHY IS IT SO IMPORTANT??!! I’m sure these are the questions you are all asking yourselves as we sit through these lectures and tutorials still not 100% comprehending how this works. But never fear… I will challenge to break this down for you.
Firstly, Senior Lecturer at Monash University, Asad Khan States. “Big Data relates to very large sets of data collected through free or commercial services on the internet” (2014). Okay cool, BUT WHAT DOES THIS MEAN?!
Basically, every click you make, every scroll you take is recorded onto big computers whose sole purpose is to store data. What people do with this data is up to them, but to make it simpler, Darryl Woodford gave a very good example with the use of Twitter. Using data gathering, processing and analytics through the means of #hashtags, Twitter is able to track trends and coordinate discussions within the twittersphere.
To break down the levels of communication, tweets have then been split into three different levels including macro, meso and micro, which is an indication of the reach of a particular tweet (Bruns & Moe, 2013). Macro means they are a part of the ad hoc publics and rapidly form and dissolve, while meso are personal publics which accumulate slowly and are relatively stable. Lastly, micro are a form of interpersonal communication and are temporary and fleeting.
So now that we know what it is… how does it learn from us? You know how when you’re scrolling through Facebook and you will get the suggested ads pop up, and somehow they are creepily accurate to things that you have been looking for? That’s big data at work. Companies such as Google will often sell their data to other companies so they can then personally target demographics that will more likely buy their products (Erickson, 2012).
http://mashable.com/2012/03/01/google-privacy-data-policy/#gallery/5-things-google-is-doing-with-your-data/50bdf2d2b589e434570049c6
However the problem with this is that many people feel like it’s an invasion of privacy. Personally, I love the idea of this and the possibilities it means for the future, especially in health. Through the use of apps and online data, governments and health agencies will be able to track trends of issues such as obesity and where it’s occurring more/ where it’s occurring less because of campaigns they may have created for specific areas. But why stop there? Bill and Melinda Gates’ Foundation can also use it to track disease and help eradicate it like in the case of polio through the use of data-driven planning.
http://www.gatesfoundation.org/What-We-Do/Global-Development/Polio
While Big data may be a scary concept to many, and the idea of tracking peoples every move is beyond thinkable, the benefits of this far outweigh the disadvantages.
Khan. A. 2014. “Explainer: what is big data?”. Accessed 14 April 2014. http://theconversation.com/explainer-what-is-big-data-13780
Erickson, C. 2012. “Google Privacy: 5 Things the Tech Giant Does With Your Data. Accessed 10 May 2014. http://mashable.com/2012/03/01/google-privacy-data-policy/
Woodford, Darryl. 2014. “New Media, Big Data and Telemetrics.” QUT Lecture , echo file posted May 1. Accessed May 5, 2014. https://lecturecapture.qut.edu.au/ess/echo/presentation/11dcf106-e7c9-44eb-a753-74dfff689043?ec=true
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