Thursday, November 21, 2013

Polished Analysis

I chose to use Facebook as a means of studying adolescent girls and their interactions online, more specifically how speech acts online help shape individual identities online.  Individuals, specifically adolescent girls, are aware of their audience in an online environment, and they code-switch and use language differently depending on to who they are communicating.  I started this research by identifying the participants who I would follow.  The participants in my group are teenage girls between the ages of 16 and 18 years old.  There is one boy who participates in one conversation, but his comments will not take a large role in my research.  They all live in a small town (Palmer, Alaska—approximate population 5900 in 2010), and they attend the same high school.  All of the participants are friends, move in the same social circles, and most are members of the same extracurricular activities (student government, band, etc.).  I address each participant by their initials.  MS is the first participant and the one with whom all the other participants are associated.

My first data set is from a post that originated on MS’ wall.  See Figure 1 for the original data set.  The thread started as a meme posted on MS’ wall, in which she was tagged along with three other individuals, so a total of five participants.  The thread then elicited 25 comments.  The data set includes comments from five people, one male and four females.  This particular thread helps me with my research because it includes multiple aspects of digital literacy.  For instance, I’ve noticed the following—typographical differences between comments, the use of internet speak, the use of emoticons, different uses of vernacular, and some numerical data.  

My second set of data is slightly different from the first set in the sense that it includes far more items to research.  See Figure 2 for original data set.  One of MS’ friends made a video about the most influential teacher she had in high school.  She chose the music teacher at her high school, and then she tagged all the other students who were in the same program.  MS did not comment on this particular post, but there were many other people who did.  There are also some adult influences in this post that were not present in the first data set.  This adult influence made me realize how intrinsic audience awareness is, even to adolescent girls.  I focus specifically on the difference in the language used in the presence of adults, even if it is in an online community.  The internet speak and use of vernacular is significantly curbed in my second data set.  Not that it is particularly interesting, but I did find that the high school students changed the way they use language when they are communicating with adults.  I do think it is interesting that it still happens online and not just in person conversation.  

My major argument is that adolescent girls invent an online identity, specifically an identity on Facebook, and that identity is tied to gender and the language used on their profiles, posts, and comments.  I also assert that the identity one establishes or creates can be modified depending on the audience with which one interacts.  For instance, in my second data set there are a large number of adolescent girls interacting in a thread that is related to their school environment.  The language used in this data set is different from the first, and I posit that it is different because the audience has changed.  The first data set included five participants, while the second included 45 participants.  All five of the individuals from the first data set were included in the second data set; however, so were many others.

In terms of actual data, the majority of my analysis comes from my second data set.  While the first data set is interesting, its main focus is to situate the reader/viewer into the conversation, and most importantly, it allows the reader/viewer to understand how this particular cohort of adolescents interact with one another on a smaller scale.  Then the second data set allows the reader to see how they interact on a larger scale with different people present in the conversation.  For instance, the information presented in the first data set shows nine instances of emoticons and three instances of overt use of non-standard conversational written English.  However, the second data set has zero emoticons and only three instances of of overt use of non-standard conversational written English.  I use overt in the sense that these adolescents are making language choices that are outside the norm of standard conversational written English.  This information leads me to assert that adolescents are aware of their audience and they purposely code-switch depending on to whom they are communicating.

I researched three terms that I thought were the most important—gender, language use, and identity.  I chose these particular terms because they yielded the best results.  I found gender to be the least important to my particular research; however, it is still important.  I look at how gender is used online versus in a face to face situations and how “slut-shaming” is used as a policing function among adolescent girls.  I also focus on language use and how it functions in chatrooms, instant messages, and on Facebook.  These particular functions of language help to distinguish how adolescent girls code-switch depending on their audience.  The third concept I focus on is identity, and I found this to be the most important in terms of my particular research because it is more of a combination and composite than its own specific classification.  The articles I chose focus on identity and how individuals express their own identities online.

Overall, I find that online identity is certainly related to language use and gender when it comes to adolescent girls.  Adolescents, especially girls, focus on their audience and use that information to code-switch between the different groups of people.  

I need some additional help finishing my conclusion.  Please help!

Figure 1


Figure 2



Works Cited
Bailey, Jane et al. “Negotiating With Gender Stereotypes on Social Networking Sites: From ‘Bicycle Face’ to Facebook”. Journal of Communication Inquiry 37.2 (2013): 91-112. Web. 31 October 2013.
Carr, Caleb T. et al. “Speech Acts Within Facebook Status Messages”. Journal of Language and Social Psychology 31.2 (2012): 176-196. Web. 31 October 2013.
DeVoss, Danielle N. and Cynthia L. Selfe. “‘This Page Is Under Construction’: Reading Women Shaping On-Line Identities”. Pedagogy 2.1 (2002): 31-48. Web. 15 October 2013
Herring, Susan C. and John C. Paolillo. “Gender and genre variation in weblogs”. Journal of Sociolinguistics 10.4 (2006): 439-459. Web. 31 October 2013.
Knobel, Michele and Colin Lankshear. “Digital Literacy and Participation in Online Social Networking Spaces”. Digital Literacies: Concepts, Policies, and Practices. New York: Peter Lang Publishing, Inc. 2008. 249-278. Web. 30 September 2013.
Merchant, Guy. “Teenagers in cyberspace: an investigation of language change in internet chatrooms”. Journal of Research in Reading 24.3 (2001): 293-306. Web. 31 October 2013.
Schwartz, H. Andrew et al. “Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach”. PLoS ONE 8.9 (2013): 1-16. Web. 31 October 2013.
Tagliamonte, Sali A. and Derek Denis. “LINGUISTIC RUIN? LOL! INSTANT MESSAGING AND TEEN LANGUAGE”. American Speech 83.1 (2008): 3-34. Web. 31 October 2013.
Thomas, Angela. “Digital Literacies of the Cybergirl”. E-Learning 1.3 (2004): 358-382. Web. 15 October 2013.
Williams, Bronwyn T. “‘Tomorrow will not be like today’: Literacy and identity in a world of multiliteracies”. Journal of Adolescent & Adult Literacy 51.8 (2006): 682-688. Web. 31 October 2013.

No comments:

Post a Comment