Nina Glatthorn (Blue)
Alex Krupp (Blue)
Our own analysis of computer mediated social support was based on the schema of Braithwaite et al. Target messages were taken from the Google Groups interface to the Usenet Newsgroup soc.support.transgendered. The first twenty top-level responses were each examined independently by the three coders and rated on a binary scale for the inclusion of the different support categories. A table summarizing the results of the analysis is shown below.
The concordance factor – the degree to which the coders' analyses were similar - for the sample was .85. Since a significantly high concordance factor indicates a more reliable data set, it is possible to examine the data further. In the twenty messages, there were fourteen (70%) instances of informational support, four instances of esteem support and four instances of emotional support (20% each), and two instances of network support (10%). Within the set there were no instances of tangible assistance or humor.
In terms of the relative frequency of social support categories, our findings were significantly different than those of Braithwaite et al. (p < 0.05). Braithwaite found that emotional support was most common in the messages that she analyzed, while we found information support to be the most prevalent. Braithwaite notes that “information support is most useful and prominent when the recipient can control the situation and put the information to use.” She speculates that emotional support was more prevalent because of the fact that health problems and disabilities are not under the control of the members of the network. In contrast, members of the cross dressing network were often confused about their situation and therefore actively asked fellow group members for advice and information. Another main difference in our data set was that network support was quite rare. Braithwaite speculates that network support was so important to those with disabilities because of the fact that disabilities often constrict social networks. In our situation, the need for social support seemed to be fulfilled by other members of the Google group.
Another possible explanation as to why our analysis yielded different results is the discrepancy in the sample size (n = 20 vs. n = 1472). In order to be validated, our experiment would need to be reproduced over a much larger sample. If such were to occur, it is reasonable to believe that the relative magnitude of support categories would be similar across the two studies, as there are cross-cultural similarities underlying the notion of social support.
Overall the transgendered community has a solid support group. We were surprised. But looking at Walther’s analysis of online support groups, it makes sense. First, Walther is correct about the greater expertise available. Only a very small percentage of people in any given physical community have experience with transgender, so by aggregating expertise the participants gain access to a much richer forum. The asynchronous and distributed nature of Usenet enables a plethora of options for both access and interaction management, another two of Walther’s factors. The benefits here were tangible; our analyses depended on messages from around the world and around the clock.
Perhaps the most important factor though was the anonymity, both perceived and real. The original poster wrote under a pseudonym, which in this case almost certainly increased self-disclosure. (The stranger on the train effect.) This leads to increased self-disclosure in replies, which creates an environment that is more supportive, both intellectually and emotionally.
2 comments:
We found very similiar things in our support group as well. We, like you guys, had people giving and recieving more informational support than we did emotional support. Today in class when people raised their hands if this too was the case for them, the majority of the class agreed. So Braithwaite is wrong? Clearly support groups for people with disabilities recieves a higher number of emotional support rather than the informational. But since we picked more ambiguous topics, maybe more people throught they would share an experience or information to help get this stranger help? Who knows, but it is all really interesting to think about.
My group found a similar result, that the topoc of support played a large role in our ability to analyze the information. In your case I would have expected more esteem support in terms of telling others that people support your life-decisions as was the case in my groups analysis on people looking for dieting advice. However, since convievably there is a lower population of transgender people than people dieting, information was clearly the most sought after piece of advice in your experiment. Maybe Braithwaire has failed in predicting a general schema for how the data would present itself against a very broad selection of data.
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