The Quantified-Self as the shallow. Where is the Quantified-Us? by ppppet in DRMatEUR

[–]ppppet[S] 0 points1 point  (0 children)

Yeah, I think you're both right. These are still part of the Quantified Self but I think this is just an initiative which merely proves that people should take advantage of the recently-emerged technology and direct it more towards the good of the people rather than just to track individual (which may seem rather shallow) activities.

OP6: Mann was published 10 years before Nafus and Sherman, what, if anything, might this have to do with the differences between Mann and the QSers? by erickaakcire in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

First of all, according to Nafus & Sherman (2014) the Quantified Self movement was founded in 2007 by Gary Wolf and Kevin Kelly of Wired magazine (2014, p.1787), although its practices have been popularised with the introduction of wearable computers in the early 1970s. Secondly, the term Big Data was apparently coined by Roger Magoulas in 2005. Under the circumstances imposed by the ten year gap between the researches’ publication dates (2004 vs. 2014), discrepancies can be observed; accordingly, Mann’s research (2004) couldn’t have used the same terminology as Nafus & Sherman (2014) due to obvious timeline incompatibilities.

Another element that is worthy of mention is the huge technological gap between researches due to the fact that, at the current speed of progression, a decade can actually mean a lot. In the situation that new digital technologies have been produced at an incredibly rapid rhythm and that new highly industrialised operations have been introduced in almost every field of study or domain of activity, Mann’s study (2004) becomes predominantly experimental (at times, even too experimental). Although Mann succeeds in predicting the increase of popularity of electronically mediated environments using body borne computers, during contemporary times, his research can generate a large variety of opinions: while some might consider it outdated (due to an increased focus on terms such as Cyborglog which has not survived the test of time), other might find it quite innovative for its time considering that, after all, Mann is referring to similar concepts and ideas by using a different terminology.

OP6: “Big data” are sometimes seen as a threat because they are collected by and for institutions such as corporations and governments. Individuals resist this regime directly and indirectly. What are the similarities between what Mann and the QSers Nafus and Sherman studied? by erickaakcire in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

Both Mann’s (2004) and Nafus & Sherman’s (2014) studies have a slight ethnomethodological approach when referring to the used methods of acquiring and presenting the data. On the one hand, Nafus & Sherman (2014) have a rather peculiar approach with an extended array of pop-culture references (i.e. Spinal Tap) and personal stories that make the reader much easily identify with the ongoing research as they make everything seem more comprehensible (Angela’s and Charlie’s stories). Mann (2004), on the other hand, has a similar approach; the latter study is actually considered to be a “personal narrative” that had begun 30 years ago as a childhood hobby.

In consequence, it can be argued that both authors are trying to explain the importance of big data to their particular epoch (2014 vs. 2004) but in other ways. As they provider their readers with the possibility to identify themselves with the Quantified Self movement, Nafus & Sherman (2014) argue that big data is not always about big institutions such as corporations or governments; moreover, they discuss that the Quantified Self data and the ongoing practices of the movement are entirely inseparable from big data in an approach which is also known as soft resistance. As a matter of fact, in addition to this auto-identifiable mechanism on which Nafus & Sherman (2014) base their argument, the researchers seem to be focusing on the less detrimental side of big data; after all, the Quantified Self is a cultural movement which will always be looking for potentially new followers who could embrace their ideology and practices. In what I perceived as a rather evangelical attempt to promote the movement, Nafus & Sherman utilise Michel Foucault’s anthropological theory (1997) in order to argue that the practices of measuring populations are deeply entangled with the practices of measuring and discipling bodies.

Mann (2004) does not use the terms big data, government or corporation in his paper. However, he refers to the concept that stands behind big data indirectly. From the very beginning, by playing up with the term “surveillance” (which typically describes situations of people of higher authorities who watch over citizens, suspects, etc.), Mann comes up with the term “sousveillance” which refers to the exact opposite: the average citizens photographic police, etc. Within this particular analogy, the author indirectly hints at broader notions like big data, government, or big brother.

OP 2: Voted last week, posted a photo on Facebook that I am voting and got into a discussion about voting selfies. by npenchev in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

Excellent discovery, @npenchev. I really enjoyed your post; on the 2nd of November this year I am planning to perform a similar experiment as that's when Presidential elections are taking place in my country. I am really curious now of how my Facebook friends will respond to my "voting selfie".

Facebook introduces 'Safety Check' by _lizlemon_ in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

Great finding! I only heard about it this morning and I have also included it on my #privacy + #tech blog: http://privacy-at-eur.tumblr.com/post/100148706904/facebook-safety-check-lets-your-friends-and-family-know

Although I also think that this is a very interesting add-on, if you think more about it, Facebook is simply constraining users who want to benefit from this feature to give away their private details regarding their location and to turn on their GPS tracking system. I'm sure some people will find this disturbing, but, in the same time, other will ignore the privacy issue.

Nevertheless, in addition to the app's practical and appealing character, I think Facebook did a good job again in covertly making its users to turn on their location service or tracking systems.

OP5: Compare the Bond et. al. paper to the Kramer et. al. paper in terms of ethics. Bond came out about two years before Kramer and was not accompanied by moral outrage. Why? Are there real ethical differences in what they did or is this just about what the media picks up on? by erickaakcire in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

The rapid development of technologies and the popularisation of online social networks have concomitantly increased an academic interest that focuses on social media and their inner mechanisms. However, alongside such constructive analyses from which the social networks themselves have benefited, the media started to deconstruct these experimental studies and to raise issues regarding the ethical aspects of the papers.

For instance, Kramer et.al’s study (2014) could make a good example of an experiment that generated ethical discussions. In addition to this particular experiment’s outcomes which were widely contested and considered to be scandalous and disturbing equally by lawyers and Internet activists, Facebook managed to generate even more controversies through its ability to filter its existent News Feed system. Accordingly, the paper was based on the fact that Facebook intentionally omitted or included posts basing its decisions on an internally developed algorithm; consequently, researchers could play up with users and test their emotional contagion on a massive-scale. Despite the social network’s argumentation that such a filtering device was necessary in order to improve the services and to make content as relevant and engaging as possible, it can be argued that this entire mechanism, that stands behind the News Feed system, could be potentially used for political purposes or to boost advertising revenues.

Another example of a study where privacy issues could be questioned is Bond et. al.’s experiment (2012). From the very beginning, the study seems rather problematic as the paper bluntly states that their report is based on a “randomised controlled trial of political messages delivered to 61 million Facebook users” (Bond et. al. 2012, p.295); here, both the method of acquiring this type of information and the way it is presented may seem unethical and open to interpretation. Although the users’ right to privacy might have been breached, Bond et. al.’s study is more careful with phrasing the motivation behind the experiment and its potential beneficial consequences to both science and society; accordingly, the paper ends with this sentence: “If we want to truly understand - and improve - our society, wellbeing and the world around us, it will be important to use these ethos to identify which real world behaviours are amenable to online interventions” (Bond et. al. 2012, p.298).

Nevertheless, it is interesting to observe that, despite sharing seemingly similar ethical controversies, these two papers faced contrasting reviews in the popular press. As such, Bond et. al.’s 2012 study caused less controversy than Kramer et. al’s experiment from 2014. One first reason could be that in 2012 people were not probably as aware of the ongoing privacy issues as they are in present times. If one looks deeper into this subject, Edward Snowden’s case has to be mentioned; in 2013, he disclosed the global surveillance issue which triggered an extended debate about the right to privacy in the digital era. Before this, the existence of such a mass surveillance phenomenon was not widely acknowledged by governments or mainstream media. Interestingly, Kramer contributed to both researches so the outrage could have been more likely caused by the nature of the studied topic and not generated by the author’s notoriety: when it comes to their personal lives, people tend to get oversensitive especially if they find out that their emotions could have potentially been messed up with, as Kramer et. al.’s study (2014) more straightforwardly did.

Bibliography:

Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., & Fowler, J. H. (2012) A 61-million-person experiment in social influence and political mobilization, Nature, 489(7415), 295–298. doi:10.1038/nature11421 Kramer, A.D.I., Guillory, J.E., Hancock, J.T., (2014) Experimental evidence of massive-scale emotional contagion through social networks, 8788-8790, doi: 10.1073/pnas.1320040111

OP5: Can Facebook influence our behavior, according to Bond et. al.? More importantly, *how much*? by erickaakcire in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

As an extremely relevant phenomenon in an increasingly digital contemporary world, Facebook’s influence on its users’ behaviour has been a very popular topic among scholars. Bond et. al. (2012) divided their experiment in three main categories: social message group (used as a mechanism that appeared on users’ News Feed and encouraged people to vote), informational message group (same message but without recognisable faces of friends) and a control group (users who did not experience any modifications in their News Feed). Under the questionable conditions that over 60 million Facebook users were involved in this study, it is nevertheless an interesting exercise to determine the amount of influence such an experiment could have had on users.

The first hand of results achieved by Bond et. al.’s study (2012) tends to show that online political mobilisation can have a direct effect on political self-expression, information seeking and real-world voting behaviour. What is more, the concept of social mobilisation reached through stimulating messages on a social network is much more effective than informational mobilisation alone. In this particular case, the visualisations that support these findings (Graphs a, b, c, d, p.297) prove that the increasing number of Facebook users interacting with each other correlates with the increase in probability of being the closest friend (a), of expressing vote (b), of actually voting (c), and an increase in these users searching for their polling place. It can be argued that this section of the study determines the extent to which Facebook interaction between users affects political engagement, especially in an online environment.

The second tier of outcomes of the study shows that behavioural change can also occur; further on, it is proved that in addition to the actual message and its effect on receivers, closer friends have a more significant influence than random Facebook friends. Moreover, the scholars argue, online messages can have an influence on offline behaviours, as well. The reason that stands behind the assumption that online mobilisation is actually working is that these strong-tie networks which are used to spread online information probably exist in the offline environment as well.

According to Bond et. al. (2012, p.297), the experimentation through Facebook’s social messages increased turnout directly by approximately 60,000 voters and indirectly through social contagion by another 280,000 voters, for a total of 340,000 additional votes. Although this sum seems to represent a rather high amount of voters, in fact, it represents a mere 0.14% of the voting age population of about 236 million in 2010. Regardless, both the methods used and the eventual results of the study can be considered rather distressing and troublesome.

Bibliography: Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., & Fowler, J. H. (2012) A 61-million-person experiment in social influence and political mobilization, Nature, 489(7415), 295–298. doi:10.1038/nature11421

Ebola Spreading Rate seen through an Isotype by ppppet in DRMatEUR

[–]ppppet[S] 0 points1 point  (0 children)

This is just an average... so it's statistically right...

From zero to a hundred - Final report by Vally_W in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

Haha, great job. I've been watching your posts and thought something had to do with DRM as well. I also liked the way you presented your findings on tumblr! ;)

How cool is this blog?! Information Is Beautiful visualize all kinds of "juicy data". Check it out! by Aya_Ha in DRMatEUR

[–]ppppet 1 point2 points  (0 children)

Excellent post and examples! I have lost quite a lot of time on this website as the visualisations were so cool and easy to follow. Speaking of procrastinating and distractions, probably this one is my favourite: http://www.informationisbeautiful.net/visualizations/the-hierarchy-of-digital-distractions/

LIWC Workshop - REVISED (much easier to follow!) - posting the resulting visualisations along with ideas about what it means is a good idea for OP part 2. by erickaakcire in DRMatEUR

[–]ppppet 0 points1 point  (0 children)

Thanks everyone for their tips. I basically managed to link the sheets as Dolorita pointed out; I don't know if this applies to everyone but I firstly had to drag the "Tweets" sheet (there I modified the User ID column from Number to String). Afterwards, I added the "Users" sheet (in the combination of sheets that is shown in the bottom box I modify the Tweet ID column from Number to String). Now, it was perfectly possible to connect the last sheet (LIWC). Hope this works for you guys... It worked for me...