Friday, November 20, 2009

Facebook and MySpace: Reflection of Perceived Norms and Socioeconomic Status




It's my individual project. :)

Research questions:
How does online inequality play out in the online social networking sites MySpace and Facebook?
What types of demographics appeal to MySpace vs. Facebook?
How does Facebook motivate "honors kids," white kids, rich kids, and kids of higher socioeconomic statuses to abandon MySpace and join Facebook?
How does danah boyd's observations about teenagers on these social networking sites translate into the actions of high-school graduates? In other words, what adults join Facebook over MySpace and why?

Sites used:
www.facebook.com
www.myspace.com
Both are global social networking sites that allow users to add friends, send messages, leave comments, upload and tag photos, post events, etc. The main differences between each website is the aesthetic of user profiles (MySpace can be altered in "creative" ways, whereas Facebook cannot) and the ability to post music to one's page (this enables many bands to have MySpace profiles, where Facebook is more likely to represent individuals or organizations).

Literature Review:
http://group-processes-social-change.blogspot.com/2009/09/digital-inequality.html
I used Elyse's post on our class blog to find the main article I used to illustrate the MySpace-Facebook divide.

http://causeglobal.blogspot.com/2009/07/white-flight-online.html
This is the article Elyse's post on our class blog led me to. The article from Cause Global: Social Media For Social Change's blog titled "'White Flight' Online?" summarizes Net researcher danah boyd's observations regarding the idea that "long-held social divisions of race, class, and income are beginning to play out online, particularly among teens now choosing which social network they prefer, MySpace or Facebook" which boyd presented at the Personal Democracy forum in New York last June.

http://www.danah.org/papers/essays/ClassDivisions.html
This is danah boyd's initial article, published in 2007, based on her observations about the class differences between teens switching to Facebook or sticking with MySpace. Boyd cautions that this is not an academic article but is rather her observations in the field; however, boyd had "analyzed over 10,000 MySpace profiles, clocked over 2000 hours surfing and observing what happens on MySpace, and formally interviewed 90 teens in 7 states with a variety of different backgrounds and demographics. But that's only the tip of the iceberg. I ride buses to observe teens; I hang out at fast food joints and malls. I talk to parents, teachers, marketers, politicians, pastors, and technology creators. I read, I observe, I document," according to boyd's description of her methodology. Also, the article published two years later on Cause Global clearly shows that boyd's research had progressed, and she had conducted interviews and gathered more data on the topic.

Data collection:
I used the articles above to flush out my own assumptions about the MySpace-Facebook divide and to present boyd's data to the class. I also observed my own friends on each networking site (610 on Facebook and 339 on MySpace) to make some general assumptions about who joins Facebook after high school and who remains active on MySpace.

Conclusions and connections:
Boyd's data concluded that teens who were wealthier, white, from the suburbs, and were likely to attend college after high school were most likely to move from MySpace to Facebook when Facebook opened its doors to non-college students. However, working-class teens, minorities, and alternative teens ("emo" kids, "wangstas") were more likely to stick with MySpace. Based on personal experience and my own observations using these sites, teens who are in high school or younger are more likely to have and actively contribute to their MySpace than high school grads. Also, adults with professional careers (professors, real estate agents, psychiatrists) seem more likely to join Facebook while working-class adults are active on MySpace. I find that friends of mine who went to or are attending universities are more likely to be on Facebook and to have abandoned MySpace altogether, whereas friends who still live at home with parents, attend community college or do not attend college at all, have children, or are extremely involved in music are more likely to still be active MySpace members (even if they also joined Facebook to keep in touch with other high school friends). I have noticed a significant number of my friends who are members of both sites share different information on each site as well. For example, friends from high school who now have children are more likely to post many photos of their children on MySpace than on Facebook.

Future Research:
I would be interested in coding and analyzing either a random sample or the first 100 of my friends alphabetically on each site to see if there is a significant socioeconomic and academic difference between MySpace and Facebook users. I would also be interested to observe my friends who are members of both networking sites to see which site they more actively participate on, and whether this corresponds with their socioeconomic and academic statuses, along with their number of children. I also got some great suggestions in class about ways to use Quantcast, ways to code different demographics, and other factors to consider when doing further research.

Social Identities on TV Tropes Wiki and Wikipedia

Research Questions: What social identities form on TV Tropes Wiki? How does identity formation on TV Tropes differ from that of Wikipedia?

Research Sites: tvtropes.org, and as a point of comparison, wikipedia.org.

TV Tropes is a wiki, the purpose of which is to catalogue the various conventions, or "tropes," used in various media, including but not limited to, TV, movies, anime, western animation, fanfic, manga, theater, and literature.

Data Collection:

I chose four trope pages from TV Tropes and four Wikipedia entries to examine discussion between users. I chose two from each site using each site’s “random” tool. The first entries that came up that 1) had at least two users interacting with each other on the talk page, and 2) for TV Tropes, were pages for tropes and not particular media items or indexes, were chosen. Two more were chosen from Wikipedia that had “Featured Article” status, based upon the front page area allocated to the daily featured articles, and two from TV Tropes that I evaluated as well-referenced and common were chosen, based upon the previous experience that I had with the site. The criteria for choosing these latter four were based upon finding tropes/entries that had a lot of discussion on the talk pages, so as to better evaluate interaction between users. My eight choices are as follows:

TV Tropes

Wikipedia

Magnificent Mustaches of Mexico

Italy-Yugoslavia Relations

Prophecies Rhyme All the Time

Peter Mogila

Most Common Superpower

I Don’t Remember (song)

Adaptation Distillation

Grim Fandango

For a quick look at user pages, I looked at the user pages of eight users from each site, chosen from the eight trope discussion pages. From Wikipedia, I chose PaxEquilibrium, Irpen, Randomblue, Sabre, Rjecina, Mzajac, Samuel Sol, and Masem. From TV Tropes, I chose Silent Hunter, Glenn Magus Harvey, Ununnilium, Cassius 335, Martello, Endlessnostalgia, Tabby, and Osh. I also looked deeply into various pages of both wikis that are specifically oriented towards the contributors. The pages that I was searching for had various purposes, such as setting out various rules and guidelines for editing, expressing social norms, and giving contributors an outlet to mitigate social strain and better establish community.

Theory

Burke and Reitzes- “Identity and Role Performance”

As a part of their study, Burke and Reitzes discuss the importance and weight of identities, indicating that they are social products, self-meanings, symbolic, and reflexive, but also act as catalysts for actions that result in the confirmation of the identity (242). Thus, a perceived identity can mean greater commitment for the wiki editor, allowing the wiki to thrive. They discuss cognitive and socioemotional bases for commitment (244), which are based on extrinsic praise and on social ties (e.g. being a part of a “posse” in which all participants act similarly), respectively.

Findings/Analysis

Trope/Entry Discussion

Discussion on the talk pages naturally followed the same sort of purpose- for editing the pages that they correspond to. However, while most discussions on both sites generally remained on-topic, TV Tropes users were more likely to respond with snarky comments. This was especially prevalent on the discussion page for “Most Common Superpower,” which is a trope relating to female superheroes with disproportionately large breasts. TV Tropes also has forums and an area called “Troper Tales (tropers can talk about tropes that appear in their everyday lives).” There are multiple places for users to ask for help, including “Ask the Tropers” and “You know that thing where…” There is individual language on each site, as demonstrated in Wikipedia's glossary and in the use of trope names as conversational items on TV Tropes.

User Pages

An optimal site for any user to identify themselves is on their personal user page. On both sites, a user may use text, links, and pictures to personalize their place as a contributor, but Wikipedia goes a little further with the addition of the Userbox. Userboxes are small rectangles with links inside, which may indicate any number of things about the user, from the types of entries they like to edit, to the languages they speak, to their personal offline interests, to the search engines they favor, to their personal identification as WikiFauna (see below). Userboxes may also include a username for Skype or an email address, allowing users to communicate on a one-on-one basis. These allow users to categorize themselves into identities that extend beyond Wikipedia. Of the eight Wikipedia users I surveyed, six out of eight used user boxes (Randomblue did not personalize his user page, and Rjecina was banned). Wikipedia user Masem, in fact, had 33 userboxes on his page. Outside of the userbox, both sites give users the option of personalizing their pages to whatever extent they wish. On Wikipedia, most of the users I looked at listed userboxes, the pages that they contributed heavily to and the page statuses, and awards that they earned. However, on TV Tropes, user pages were a lot less detailed and a lot more casual. Four users had extensive lists of shows that they watched or tropes that they started or helped to name. Users tend to use more casual language on their pages, and user Ununnilium even created hypothetical “Magic: The Gathering” trading cards based on tropes and listed them on his user page. This would make it appear that describing one's identity on TV Tropes is less important.

Actual Roles

Both sites offer various ways to identify oneself within the wiki. Wikipedia has the concept of WikiFauna- various animals and creatures (e.g. WikiPig, WikiElf, WikiKraken, WikiWitch, WikiPlatypus) that indicate a user’s actions on the wiki (e.g. WikiFairies focus on style, color, and design on entries). While we briefly discussed roles and identities on Wikipedia in class, the detail here is tremendous. For example, there are six subsets of WikiElves. I believe that these act as a socioemotional basis for commitment, as the explicit name of the identity gives the user an idea of people who are like or unlike themselves, and whom they seek out (e.g. WikiKnights search for WikiDragons). TV Tropes doesn’t have such a direct and detailed listing of specially-named identities, but does contain common roles played on Wikis as tropes (e.g. Grammar Nazi, Hedge Trimmer). On their user pages, some users identify themselves with these tropes (Ununnilium: “by the way he (referring to self) is such a Grammar Nazi”), but because the identity is considered a trope for all wikis rather than specific to TV Tropes, the identity seems to be more of an afterthought.

Editing and Community Rules

While both wikis have deliberate structure and rules for editing, and both have a rule saying that the rules are loose, differences remain. Wikipedia has a category relating to the rules that is fairly easy to find, with each rule containing a separate detailed essay. TV Tropes does have rules under a category called Administrivia, for which I had to do a search to find. TV Tropes states on their front page, “We are not Wikipedia,” indicating a casual nature that Wikipedia lacks. TV Tropes, does, however, have in their list of Wiki Tropes, some actions that are looked down upon- more like social taboos, for instance, ”Complaining About Shows You Don’t Like (that is, on a trope page),” or being a “Bluenose Bowdlerizer (one that censors innocent text).” There are a few more widely-accepted guidelines. For example, a troper is to avoid Natter (discussion on non-discussion pages) and avoid saying “This Troper (that is, using main pages for personal stories and references).” However, Natter and usage of “This Troper” still appears often, which reflect the nature of the rules as guidelines. Naturally, the role of being a contributor or troper in general hinges on following these rules, and action that helps the wiki is often cause for reward.

Awards and Rewards

I was interested in the way that good and helpful participation on the sites incited rewards as a cognitive basis for commitment. Wikipedia users had barnstars, which a user may post on another user’s page. These are posted in userbox-type boxes, with text that the giver may add themselves. Also within Wikipedia are WikiLove templates, which are user-to-user "gifts" to be posted on user pages as a "thank you" for a good insight, a good edit, or just to spread good will. They usually take shape as various food and drink items. TV Tropes has the Made of Win award, along with sub-awards such as the Made of Forum Win. Made of Win is simply a Wiki-style page that anyone can edit, stating their nomination. If the nominated user takes notice or is notified on their personal talk page, they may post that they have won on their user page, but it is not immediately attached to the user’s personal page, unlike the barnstar. For being a good contributor, the personal nature of the barnstar and the wikilove item may have an effect on personal commitment on a cognitive basis. The Made of Win may have a similar effect, but only if the contributor notices or discovers that they even get the award.

Conclusions

From this data, I would like to suggest that while Wikipedia does not have traditional hierarchical institutional structure, Wikipedia is gaining a more institutional flavor because of its structured nature. The various subtypes of WikiFauna delineate specific duties and roles to play, offering a well-structured in-site communal atmosphere. On TV Tropes, these roles are not prescribed. The casual and humorous language used on the user pages and discussion areas create a social atmosphere of social that is more user-mediated, rather than institutional.

I’d like to suggest that participating on these wikis allow users to demonstrate commitment to identities in the offline world (eg. As a scholar or person of some knowledge, as a fan). However, identities on TV Tropes are more often self-formed and sometimes pre-existing as part of offline society (e.g. I'm a fan of House offline, I'm a fan of House on TV Tropes). People can act more like their casual, everyday selves on TV Tropes, rather than having to take on a staunch, scholarly identity that Wikipedia’s rules might enforce. TV Tropes’ success thrives on the devotedness of the users to their specific media of choice or media in general (that is, if there is no media, there is no TV Tropes), whereas the structure of Wikipedia allows it to act as more of an institution.

Work Cited: Burke, P.J. and Reitzes, D.C. (1991). An identity theory approach to commitment. Social Psychology Quarterly, 54(3), 239 – 251.

Thursday, November 19, 2009

Reviews as group-forming.


I chose to do my project on Urban Outfitters--specifically, their reviewing feature. I chose this mostly because I like Urban Outfitters and spend too much time looking at items anyway. I also chose it because I would never have thought of reviews as group-forming before taking this course, so it seemed to fit well as the last project for this course.

Urban Outfitters is a store (both online and tangibly across several countries) which sells women and men's apparel and accessories, as well as housewares. Several years ago, a review feature was implemented, so that people who purchased the item could give their response to potential buyers. A question-and-answer section was started within the past year as well, to combat users who were asking questions in the review section. A tagging section was also recently added, where users could describe an item as "cute" or "80's" or whatever else.

For my project, I coded 108 reviews that had received a vote for “Was this helpful to you? Yes/No.” These were all from the non-sale dresses section.

I coded the amount of up-votes versus overall votes, the person’s username, the number of words in their review, if they were a top contributor, the three separate ratings they gave the product (overall, fit, and look).

Then, I coded for 11 individual variables present in their review.I coded for the following within the review:

1. Tells a story, ex. “When I saw this...,”

  • “As soon as I opened the box...”
  • “I read a lot of positive reviews...”

2. Sizing, ex. “I’m 5’4” 110 pounds”

  • “I’m curvy and...”
  • Or mention of what size they purchased

3. Quality, ex. “The material felt cheap.”
  • “The zipper broke as soon as I unzipped it.”

4. Price, ex. “This was worth every penny.”

  • “Great buy.”
  • “This was not worth what I paid for it.”
5. Wearability, ex. “This dress is too short.”
  • “I didn’t have to wear a bra with this, yay!”
  • “The dress rode up.”
  • “The bottom is see-through.”
6. Fit, ex. “This hugged in all the right places.”
  • “The medium was too loose.”
7. Comfort, ex. “This was tight across...”
  • “This was comfortable.”
8. Appearance, ex. “Cute!”
  • “This dress is so pretty.”
9. Direct recommendations, ex. “You should buy this!”
  • “I would wear this with tights.”
10. Indirect recommendations, ex. “This was obviously made for skinny girls.”
  • “I paired this with tights, and it was perfect.”
11. I also coded for responding to other reviewers, but I ended up not including this in the ten variables. However, examples were, “I agree with...,” “I didn’t find the material to be cheap.” I ended up not using this data, however.

After coding for all of this data, I then added up the number of conditions met by each reviewer. The possible number was 10. The highest reached by a reviewer was 9. The lowest was o (However, this was only one review--which was less of a review and more of a “UO, Get more in yellow!”). The average was about 4.79.

I then found the percentage of a review’s positive feedback, for simplicity reasons. The vast majority were 100% positive, but the average was 86.74%.

Findings:
(click for a larger image)



(Professor Welser suggested that I redo this chart so that you can see concentrations of points--which is a great idea! That would give me a better idea of what I'm actually seeing in my findings, because currently, it doesn't look like much.)



In conclusion, although there seemed to be a small shift towards more up-votes if the reviewer met more conditions (ie offered a wider range of information), this was pretty miniscule (a difference of only one condition).

So, there is not enough evidence to suggest that offering a more complete range of information makes readers more likely to up-vote you. It was also difficult to collect this information because the majority of reviews received only one vote. And, for about every 5 reviews, only one would be rated at all. The reviews that received 6 or more votes were very out-of-the-ordinary.

In the future...
  • I’d love to play around with the data I’ve collected so far--perhaps find the “necessary conditions” that, on average, must be met to receive up-votes.
  • I’d also like to explore the reviews that received more than 1 vote, because they didn’t seem to follow any sort of pattern.
  • I was able to qualitatively observe a lot of interactions during this process--for example, although there were “top contributors,” their reviews were frequently useless, like, “This dress in white is so cute!” Urban Outfitters encouraged these kinds of reviews by offering top reviewers occasional discounts, but being a “top contributor” depended solely on how many reviews a person added, not on the quality of them. Instead of looking to these reviewers as helpful experts, I think that many readers saw them as annoyances.
So, what do you think? Comments? Suggestions?

A Tunable Network Simulation (Thusly Tuned)

The continuation of my project has been the creation of a tunable social network simulation. The first addition to the project is the addition of more means of control including the size of the population and the structure of the functions that serve to create the networks. The more dominant addition has been the inclusion of an increased number of metrics for evaluating the properties of the simulated graph against the properties of a real social network graph.
The first measured property, frequently referred to as the property being of scale free, is the distribution of degrees in the network. Degree distribution in social networks tends to follow a long tailed distribution with most individuals having a relatively small number of edges to other nodes and a select few having a large number of edges. The quality of being scale free can either be evaluated as a direct comparison of the distribution to the expected distribution or as a Power Law exponent indicating the overall distribution. Measuring the distribution of degrees also lends itself to the inclusion average number of degrees as a part of the desired creation of a scale free network.
I also added measurements for clustering and grouping. I measured the clustering coefficient, and the number of bicomponent clusters. The clustering coefficient measures the degree to which nodes are tightly connected, where as the number of bicomponent clusters provides a rough estimation of the number of distinct groups present in the graph structure. Also examined, though not formalized in a metric examined for each generated graph, was the distribution of clustering coefficients which, similar to the distribution of degrees, should be non-normally distributed and tend towards a long tailed distribution.
So what do all these new inputs and outputs mean? We can adjust the inputs of the simulation and see if we get better outputs! In an unprecedented feat of interactivity I supplied the class with a set of simulation inputs and suggested that the output of the clustering coefficient was higher than expected. An arbitrary audience member (Read: Ted) made a suggestion and when we adjusted the inputs we got a graph that more closely resembled what we might expect from an arbitrary social network. Below is our co-constructed graph as well as the distribution of edges:

High vs. Low Risk Transactions on ebay.com

 Sellers on Ebay exploit a wide range of low risk transactions (books for example) as well as a variety of high risk transactions (selling electronics). Is it risky for consumers to resort to purchasing expensive, more in depth products over simpler, cheaper ones through the internet? Or, is there trust established because of the quality of the “high risk” product assuming if the seller puts something of such expense out there it is reliable?

Books presented on Ebay range from about $7.00-$35.00. They only have so many reviews, when in a large range of reviews on such a small scale of 5/5 it is hard to establish how reliable that product is. The “product details” of each book is pretty lengthy, advertising low risk products in a descriptive way. Review scales for electronics differ from books, measure by “positive feedback” percentage scale. Most electronic sellers offer free shipping. Example of attempting buyer/seller trust. (“what will you get for me?”). The sellers information directly right of product picture and information for someone to access questions. However impersonal, exploiting the seller through a screen name rather than their actual name. Location of the item itself is available. The description of each product is short.

Assume buying electronics on Ebay hold more reviews, more reliable scale, giving other indications (seller’s personal information, location of product, benefits to the buyer such as free shipping) that they might be more trustworthy. Because High Risk sellers have so much at stake, they are almost forced to remain dependable. One bad review could cause others not to buy. Purchase based more on the picture, quality, and trustworthiness rather than a general description. Low risk purchases are more opinionated. Consumers may purchase item according to their liking, and the detailed description over the small scale review system. “Normal” people can’t really sell electronics on the internet (would have to be for a lower price). Suggestions about other comparisons??? Product types of seller characteristics??

Reputation system differ online because they perceive social differentiation. New ways to transfer information about people’s reputation. Organize, quantify information. Barriers to trying to get online feedback. Getting people to contribute? Negative feedback. Honest feedback. Reliability trust. Decision trust. Personal trust.

Higher transactions more trustworthy to the extent of how valuable products are. When given positive feedback/reviews + seller information + product information à enough evidence to build trust. However, Ballot stuffing- people can skew reputation with ratings. So…study of the reviews, people’s extent they go through before actual purchase, biased? Rigged?

How QuantCast Works

Quαantcast was originally designed to assess the demographics of website traffic so businesses could be aware of the website’s audience and advertise accordingly. This is evident as many of us have noticed how advertisements on these sites have changed to clearly target certain populations. So is Quαantcast some omnipotent being that magically generates fairly accurate demographic data? Close, but no. Instead Quαantcast uses what they call in their methodology, “the inference approach.” Simply stating, “The key to this approach is to compare directly measured data with reference points that provide known truths (for example web destinations that require registration) and to use this to calibrate models.” Not only does Quαantcast generalize demographics based on previously conducted studies, but in a more Big Brother fashion, collects cookie information from users as they visit sites, especially those which require profiles with demographic data. Also known as our digital footprints. We discussed something similar to this with the Lazer et al. article. Though Quαantcast is only publishing aggregated data without identifiers, it certainly raises some privacy issues.

What does this say about the power of businesses and advertising agencies?

How have social networking sites changed especially in terms of advertisements? For example, consider the 2008 Presidential campaign advertisements on Facebook.

Demographics of Five Top Social Networking Sites Using QuantCast

For my individual project, I looked at the demographics of five top social networking sites using QuantCast.com. Included in this analysis were: Facebook, Myspace, Bebo, Friendster, and Hi5. These sites were chosen based on their rank on http://social-networking-websites-review.toptenreviews.com/. Despite having similar benefits such as: photos, comments, friends, applications, and privacy options, different sites clearly appealed to different populations. Facebook uniquely appears to have a more affluent, educated, audience. Facebook also has the largest percentage of visitors (13%) who are age 50+. Myspace, though mostly Caucasian, has an above average number of Hispanic visitors, but also appeals to a young adult audience with no college and children who are under 18. Bebo largely appeals to African American teens, while Friendster’s audience are mostly Asian young adults and Hi5 visitors are mostly Hispanic young adult males with no college who make 0-30k per year.

What are some possible reasons for these demographic differences? Specifically, why are most of the differences related to socioeconomic status and ethnicity? Facebook, for example, may attract a crowd with a higher number college students and college graduates, because, until recently, Facebook required a university e-mail address to join. Also, as Backstrom et al. posited in their theory of diffusion of innovation, that people are more likely to join groups in which they have friends who are already members. This also relates to our previous discussions of trust and recommendations from friends who are already members of a group. What other possible reasons can you come up with for the demographic differences? You can view the charts here: http://docs.google.com/present/edit?id=0AX3vFFf18ROAZGc5NGRzZ3RfMTlnc3Bmc3Noag&hl=en. QuαntCast uses estimated data of 220million internet users in the US

An index of 100 means the measurement is on par with the population estimate.


What does this imply about the changing face of the internet? Indeed in the demographic post, we see that people ages 50+ are visiting social networking sites. Is this evident of McAdams idea of “An Esteem Theory of Norms”? Has it become a norm for people to have a Facebook, Myspace, etc.?


p.s. Forgive my poor typing and grammar. I only have the use of one hand due to surgery.

Monday, November 16, 2009

"Snark" by David Denby


Last year, I reviewed the book "Snark" by David Denby. In the book, Denby analyzes what he considers the emerging art of snark, or negative, nonconstructive and unusable comments. Although the book does not limit itself to discussing snark online, it does touch on the idea that snark is much easier to say in online, anonymous settings. How does Internet communication enable snarky comments? Another review for the book found on New York Magazine's website can be found here. I've posted the review I wrote below.

"Snark" Review:

What do New York Times columnist Maureen Dowd, celebrity blogger Perez Hilton and popular Web site Juicy Campus have in common? According to author of "Great Books" and film critic for The New Yorker David Denby, they all use a particular kind of graceless humor called snark.



Denby recently published an essay about "a strain of nasty, knowing abuse spreading like pinkeye through the national conversation." His 2009 book, "Snark" outlines the history, style and mindset behind the malicious, personal humor that has infiltrated our lives through certain TV personalities, celebrity blogging, humor print columns, social networking Web sites and other media arenas.



In 128 short pages, Denby examines the modern media world. He compares the traditional, fact-checking journalists of yesterday to modern-day bloggers and their anonymous readers who leave snarky comments. Denby not only explains how snark affects reputations using ill-humored wit, but also suggests that snark perpetuates old racist and sexist stereotypes by repackaging them as unfunny jokes.



Denby's book is insightful and conscious. He examines the recent changes in media due to technology shifts and questions the motives and actions of snarks, showing his grief for the witty, thoughtful writing of yesteryear. He writes clearly, concisely, but creatively and makes each paragraph something the reader can relate to and understand.



One of the greatest aspects of Denby's writing is his knack for research. He uses countless examples of snark to illustrate to readers the fine line between snark and true comedy, placing each example in historical context. Each of his ideas is well supported with current and specific examples, especially from the 2008 presidential election.



One of Denby's examples of snark is a headline running during a discussion of Michelle Obama on Fox News and reads, "OUTRAGED LIBERALS: STOP PICKING ON OBAMA’S BABY MAMA!" Less obvious examples include a McCaine campaign ad attacking Barack Obama. "It should be known that in 2008 the world shall be blessed. They will call him…The One," were the opening lines from the ad, which according to Denby, targeted Southern voters who see the phrase as a put-down for an "uppity’ black."



Denby uses many examples from the Web sites and TV stations a majority of us visit everyday and paints them with the scarlet letter of snark. But that doesn't mean Denby is without a sense of humor. He praises Stephen Colbert and John Stewart for their witty sarcasm and snark-free commentary. But for Denby, the fact that these comedians take ownership of their insults and generally avoid making distasteful and gut-wrenching comments without having a more serious, or at least funny, point to make leaves Colbert and Stewart snark-free geniuses.



Denby also praises Jonathan Swift, who he suggests is a "practitioner of snark-free momentous irony." However, Denby considers great poets like Alexander Pope as a lower breed. For Denby the distinction is "between harshly funny satirical writing and trivial kneecapping."



Surprisingly, Denby admits to having been accused of snark himself. Once as a movie critic, he made such sinister comments about the ridiculousness of Ben Stiller’s face that Owen Wilson threatened to "punch me out."



Denby damages his compelling argument by failing to mention his personal political bias that runs rampant throughout most of his book. Although he at one point mentions that liberals are not innocent of snark and gives one example, Denby's examples of political snark are overwhelmingly conservative. However, this may be attributed to the fact that the Obamas ran a miraculously clean campaign and republicans have tended to be more guilty of reinforcing gender and racial stereotypes.



Denby also defends the one source of snark he finds acceptable: the attack of expensive, under-performing restaurants. He praises Eater.com for ripping apart upscale restaurants that aren't up to par—but how is this different from the other types of snark Denby loathes? Scathing, heartless blogging about restaurateurs can easily shut down a restaurant as quickly as an unfair critic's theater review can kill a Broadway production. If Denby had left out this one exception, his argument would have seemed stronger.



Denby's book is certainly worthwhile, but ends weakly without a call to arms. He leaves readers without suggestions of how to not participate in snarky media and where to go to find genuine wit in an age where speed and shock value outweigh integrity.



"Scratch a writer of snark, and you find a media-age conformist and an aesthetic nonentity. Recognizing no standard but celebrity, indifferent to originality or to quality, snark may be out-of-date or fading almost as soon as it’s filed (or posted)." "Snark" examines the harsh reality of the modern ruthless media we fail to question. Denby delivers a thoughtful media critique everyone can relate to, but doesn’t offer the glimmer of hope that's needed to address this serious issue.

Viewing American class divisions through Facebook and MySpace


Earlier this quarter, Elyse made a blog post about an article on Cause Global: Social Media For Social Change's blog regarding a Net researcher's findings on "white flight" from MySpace to Facebook. That Net researcher was ethnographer, danah boyd.

Danah boyd's initial research can be found here. Although she admits that her post, "Viewing American class divisions through Facebook and MySpace," is not meant to be an academic article, she illustrates many interesting points regarding how class divisions play out among teens on social networking sites.

Comments on YouTube

For my individual project I collected data from YouTube videos, concentrating on the relationships between the following variables: # of views, # of comments, length of video, and comment/view ratio. While I rejected my hypotheses, I found a positive correlation between # of comments and comment/view ratio. It may seem obvious that videos with more comments should have a higher comment/view ratio, but I think it reveals a trend among internet usage: The average internet user is more likely to participate in a conversation if one is already going. Thus, viewers will be more likely to comment on videos that have a lot of comments already, because a dialogue has already been started. While my small sample size prevented me from being able to assert a statistically significant relationship, I think that continuation of this research with a larger "n" and slight methodological changes could reveal such a relationship.

Fashionista Comments



My project was a coding of comments in response to the "best dressed" threads on the website fashionista.com. I coded 100 comments in regards to 11 weeks of posts. My goal was to figure out how the posters on a fashion website interact and if they cultivate any patterns or form any sort of community. I coded for a variety of factors, some of which did not yield significant results when put in a graph. The factors that were significant were positive/negative comment, and the user the comment was directed at. The above graph shows direction of comments, with green representing both positive and negative sentiments, red as positive, and blue as negative.

I concluded that users with the first or second post in response to a thread had more interaction with other posters, as they received more direct responses. The topic of conversation was very specific and stayed consistent. There is a small community of fairly consistent users on this site, but no noticeable hierarchy or relational ties amongst users. The comments were mostly positive, with only 2/11 weeks having more negative responses. Also, negative comments were usually made in conjunction with a positive comment. There was less discussion of specific designers; the focus was more on the idea of "style."




Sunday, November 15, 2009

Google Wave: Trying to do Too Much?



There's been a good deal of tech buzz revolving around the release of the real-time group coordination tool Google Wave on September 30th. Though many hail the benefits of this multifaceted communication platform, others question whether Google has forgone consideration of maintaining low transaction costs in favor of luring users with a multiplicity of tools. Previous literature on collective action highlights the need for organizations to make participation an easy, low risk activity for users, but having to learn new "terminology" (wavelets, blips, robots, etc: http://mashable.com/2009/05/28/google-wave-guide/)

What does everyone else think? Has Google released the "wave" of the future or does it still need to work out some kinks in its seemingly convoluted system?

Wednesday, November 11, 2009

Music Variability Among Groups

Question: Is there really a higher musical variability among members in groups that stand for accepting a wide range of artists when compared to members of a group centralizing around one specific type of music?

Sites used:

http://www.last.fm
Last.fm is a website which records the songs that users listen to, and then compile the logged tracks into different statistics, such as top artists or top tracks.

http://anthony.liekens.net/pub/scripts/last.fm/eclectic.php
This is the “How Eclectic is Your Music Style?” tool for Last.fm, which measures how much variety can be found in a user's music library. Members type in their username, and then their top artists along with artists similar to those artists are analyzed, and a score from 0 to 100 is given, signifying a lack of variety or a great variety in music, respectively.

Data Collection: I first selected two groups on Last.fm, the first was Extensive Musical Taste and the second Female Metal Vocalists. Then I chose random recently active members in these groups and sent them all messages, linking them to the "How Eclectic is Your Music Style?" tool and requesting that they send me back their scores. Based on the responses I got, I took an average and found these averages:

Extensive Musical Taste: 89.24

Female Metal Vocalists: 72.25

Connections: The main connection with this analysis I made with the class was that of group identity and roles. I feel as though the reason the numbers came out as expected was because members join groups which have an identity they wish to portray, or at least that they would want to portray. Members may also feel that once they are a part of a group, it is their role to listen to the types of music the group promotes. Status comes into play here; members who's music libraries exemplify the music tastes of the group may gain more recognition or respect. People may come to them for music advice, or value their opinion more. Thus, members may strive to fill that role to gain the respect.

Conclusion: The data gathered found that the music group which promoted variability did have a higher variability than one which promoted one specific type of music. Group identity plays a key role here, as the reasons members join groups is to become a part of a certain identity, or to have a group which represents an identity they wish to portray.

Future: I'd like to look into whether people listen to certain types of music because they like them, or just because they wish to fill an identity, and if being a part of a group helps them feel as though they are accomplishing embodying that identity.

Affordances for Activism



The question posed by this study is as follows: How can online social movement organizations use online affordances to effectively mobilize activists?

The Benefits of Online Mobilization:

According to Postmes and Bruinsting (2002), online environments are “fit for our native desires and talent for group effort” and facilitate a convenient “collapse of transaction costs.” Despite their inherent challenges, they have the potential to unite geographically widespread but ideologically similar in a common space for democratic discussion and event campaign coordination.

Complications of Online Mobilization:

High levels of social uncertainty render it difficult for organizations to develop cohesive communities online. Additionally, there is a high risk of sabotage due to difficulties in regulation, as well as the potential for “massification,” or the obscuration of individual voices due to the volume of input (DiMaggio et al 2001).

Sites analyzed:

Change for America (www.barackobama.com), Amnesty USA (www.amenstyusa.org), Democracy for America (www.democracyforamerica.com), MoveOn (www.moveon.org)


Data and theory

This study is based on analysis of literature following two primary thematic strains: collective action and identity development. Within the former, it emphasizes organizational framing and issues related to cooperation and coordination. Within the latter, it differentiates between individual and networked identity development and the adoption of social roles. All of these elements are strongly interrelated and either facilitated or strengthened by user-to-user interaction, which reduces social ambiguity and increases interpersonal trust. By placing this analysis alongside observation of existing social networks, this study offers a picture of what tools and affordances organizations must use in order to mobilize latent readers into networks of mobilized activists (Preece and Schniederman 2009).

Data collected for this project is largely observational. In terms of quantifying data, site efficacy is divided into five categories: organizational framing, individual identity development, networked identity development, promoting communication, and developing community. Within each, affordances that help fulfill this requirement are listed and numeric values are assigned to indicate whether the site does or does not features these tools. This provides a numeric analysis the strengths and weaknesses of each.

Organizational Framing
Organizational framing refers to the way in which an organization presents itself to its constituents. Frame alignment for SMOs may tap into participants’ identity or emphasize salience in current events and overall importance. Placing strong emphasis on framing is generally characteristic of top-down organizational structures.

As evidenced by the chart, all sites analyzed exhibit excellent framing strategies. The main difference lies in the fact that some sites place more emphasis on top-down control over users’ perception of the organization rather than encouraging user contributions. All sites provide live news feeds, information about previous and current campaigns, and a history of the organization. MoveOn in particular carries this one step further by providing a section titled “success stories,” which promotes the image that if users will likely enjoy some form of payoff for costs incurred through participation. Measuring rhetoric involved searching for the prevalence of key words and phrases that emphasize the importance of the individual (“you,” “action,” “together,” or “can”) and strong language that emphasizes importance and/or immediacy (“lies,” “extremism,” “urgent”). Though its ratings are equivalent to that of the other sites, Change also distinguishes itself in regards to how it emphasized the importance of the individual to the organization.


Cooperation Coordination and Resource Management

The social remoteness associated with online environments renders promoting coordination and cooperation among participants a challenging task. This problem stems from two areas. Firstly, how do online spaces foster trust and interpersonal commitment in light of social ambiguity? Secondly, when a cohesive community has been effectively developed, how does the site facilitate communication and enhance coordination among participants? The first step toward satisfying these tasks involves allowing users to develop a strong, identity-based personal commitment to the organization and it’s objectives, both on an individual and networked level.

Individual Identity Development
Hogg et al. (1995) refers to individual identity “self-conceptions, self-referent cognitions, or self-definitions,” that are developed through the internalization of an individual’s “reciprocal relations between self and society.” Though identity is refined and reinforced by reactions from others, this section exclusively analyses the tools that allow users to independently label themselves as “activists” within the organization.

Change – a site that emphasizes self-presentation and interaction - shows itself to be a leader in terms of identity development. As evidenced by the chart, this site provides a number of ways for users to label themselves as activists, thus solidifying self-perceptions of such. Sites that involved little to no user interaction (Amnesty, MoveOn) offer some concessions in this area, although they offer few opportunities to help users strengthen and refine self-imposed identities through reciprocal interaction. The lack of online interaction facilitated by these sites suggests that they rely on activists to transfer their online interest into real life action, though the lack of user-to-user communication weakens identity development, stunts commitment and inhibits coordination.



Networked Identity Development
This section introduces an element of interaction into the concept of identity development. As emphasized by Burke and Reitz (1981) identities are social products, formed and maintained through social process. To fully understand their identity, individuals must view others’ actions, categorize these actions, and locate themselves within these categories. This section delineates affordances for identity development that prompt reactions from others and allow users to view the behavior of their fellow participants and notes their presence within each site.

Sites with embedded social networks distinguish themselves as leaders within this category. Change and DFA clearly provide the most opportunities for individuals to mirror their perceptions of self against those of their fellow users, thus strengthening their identities as “activists” within the organization. They provide pathways of self presentation such as user profiles that allow users to undergo internalized comparisons.

Identity and Role development
Social roles arise when individuals integrate into their existing identities additional expectations and obligations. Because individuals have a tendency toward personal “dissonance reduction,” individuals will likely align their actions with this role (Hogg et al 1995). Additionally, if these roles are then are salient to the individual’s strong social ties or incur a large cost if vacated, the individual is increasingly likely to fulfill the duties associated with them. Based on this, we can conclude that sites which facilitate interactive identity development - such as Change – will help users develop roles - which will in turn transform them from latent readers to motivated activists.


Community Development and Coordination

In addition to assisting with identity development, communication is also vital for developing interpersonal trust between otherwise remote users and, in the case of collective action, allowing them to collaborate and work toward a common goal.

Promoting Communication
This section delineates affordances that allow users to communicate with one another in an effort to reduce social ambiguity, promote trust, reinforce identity/role development and facilitate coordination. Again, those sites that integrate social networking systems into their basic site design (Change, DFA) excel in this category as well. By increasing the number of pathways and ease of communication between participants, these sites help ensure that users will transform their latent readership into activist engagement.

Community Development
This section analyses the coordination efforts of the organizations, both on and offline. It enumerates evidence of group formation and collective action within online environments and in real life. As shown by the chart, both interactive and non-interactive sites provided evidence of past events and used online spaces to advertise future events. This helps legitimize the organization and serves to bolster organizational framing efforts. They also verbally encouraged users to engage in offline recruitment efforts, though non-interactive sites decrease the likelihood that users will carry out this task by failing to fully develop users’ activist identities/roles and not allowing them create strong interpersonal ties on which these identities and roles depend.