I had the chance to catch a tweet this morning from Laura Fitton about the MIT Who Gives a Tweet Project and, being interested in the social media research & social network analysis, I could not help but dive in. I found it pretty interesting and thought I would share some of the insights I gleaned.
- Without context Tweets are mostly meaningless. As Doug Weinbrenner and Nedra Weinreich pointed out in a brief discussion on this, context is critical. Context, moreover, has multiple layers to it. My ratings of Foursquare tweets were universally poor because the spatial relevance was lacking. Conversations primarily directed at particular individuals (but made publicly) rated poorly because of the lack personal relevance.
- Rating other people’s content revealed my own biases: We all see the world through filters. For the most part, we are relatively oblivious to them but this exercise provided me with a good opportunity to recognize a few of mine. I saw clearly that I was more interested in reading (and clicking through) Tweets where I agreed with the content. Although I do try to keep my horizons broad, it is very easy to turn quickly away from opinions different from our own and turn toward those that mirror our own perspective. I also found myself ranking Tweets based on my understanding and interpretation of Twitter etiquette. Good content certainly suffered when it seemed like an author had not followed the “rules”. This includes Tweets that I characterize as something more akin to “internal dialogue” – personal grooming questions come quickly to mind here. That being said, although I have my own approach to participating on Twitter, it does not mean that other ways of using the platform are wrong or valueless.
- Randomness matters… but you can give it a hand: As much as context matters, I am an enormous fan of the randomness of Twitter and frequently come across very compelling content and people just by sitting back and watching. However, I did notice that Tweets without sufficient innate context (which occurs frequently on Twitter) rated poorly and that I quickly passed them over. I think this is an important consideration when imagining how individuals encountering your content for the first time will respond. I know that when I am putting out information that is intentionally “broadcast”, I will think more critically about what that Tweet might look like in isolation.
Finally, I actually think there could be value in a more user-focused derivation of this work. Personally, I would love to have some better tools engage with a small group of individuals around organizational accounts on social media. I am imagining here a continuous, distributed focus group with engaged stakeholders able to consistently interact with, crtique and evaluate content. Is this a bad idea?
So, have you checked this tool out? Have some of your own thoughts, love to hear them!
Interesting project! It certainly is humbling to see some of the responses to you own tweets. What it does really miss is the intentionality, though. Do I want my followers to like all of my tweets? Well, that would be nice, but usually I’m trying to accomplish something else.