8: Perusing Support Groups

My partner and I chose twenty different messages from various google support groups. Our results generally followed Braithewaite et al., but accuracy may have been lost since we coded fewer messages than they did.

Just as in Braithewaite et al.’s results, we too seemed to have the most conflict in deciding which messages were emotional because of the broadness of the category. When we first began searching for messages, it was easy to find responses, but as we continued, we noticed that many of the messages were simply links to articles and usually people did not respond to them. Similar to Wallace’s numbers phenomenon, – where in ftf, more people mean less helping and in CMC, there is more assistance since it’s harder to see how many people are present, so you don’t rely on other people’s reaction to the aid – the groups that had more people had more discussion/responses to questions, as opposed to the groups with few people had little or no discussion. Another interesting factor that played in finding messages with more discussion was anonymity and social distance. This not only allowed for wider range expertise available from people all over the network, but it allowed the member to self-disclose more, which provided a greater number of responses that were more interesting and personal.

I found it interesting that we actually had a few messages without information because I thought that almost all messages would provide some sort of information or advice, but that was not necessarily the case. Some messages were solely emotional in providing sympathy, or some were reactions to an anecdote. Unlike Braithewaite et al., where most of their messages were from people with physical disabilities, most of our messages consisted of members with mental disabilities (i.e. – grief, depression, loneliness), which may account for the discrepancy in the percentages of message types.

After reviewing the messages, we found our inter-rater reliability to be 90%, which is 10% higher than Braithewaite’s et al.’s reiliability. This higher reliability may be accounted for because of the lower number of messages analyzed. Our results ranked information first (75% of the messages), emotional support second (50%), esteem support third (40%), humor fourth (20%), and tangible assistance and network support tied for fifth (5%). Whereas, Braithewaite et al had emotional support first (40.0% of the messages), information second (31.3%), esteem support third (18.6%), network support fourth (7.1%), and tangible assistance fifth (2.7%). Not included in their results, was the analysis of humor in messages. We found that there were a significant amount of humor, more so than tangible assistance and network support combined, and most of them were ones that did not have emotional support in them because it is more difficult to show empathy and be humorous at the same time.

Partner - Will Hui (Blue Blog)

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