Abstract
Recent years, numerous users spend a bunch of time engaging in social networking services (SNSs). To explore whether learning occurred among users’ interactions, this study investigated an active tweeter (Twitter user), Mr. Tim O’Reilly, on a popular SNS, Twitter, as the research participant. Under his permission, the researcher collected Tim’s 463 tweets as well as tweets replied from other 617 tweeters for analysis from 1st October to 31th October 2011. This study mainly used qualitative methodology and supplemented by quantitative one. More specifically, the researcher conducted qualitative content analysis on Tim’s tweets and others’ reply tweets, and used descriptive statistics to calculate times of replies and retweets to Tim’s tweets. The results show that tweeters learn through conversations with the aid of 140-character limit per tweet, Twitter syntaxes and following networks. Three learning behaviors were generalized from conversations, including 1) sharing links and resources, 2) providing answers and solutions, and 3) making comments and adding personal opinions. To conclude, this study demonstrated that on Twitter learning is 1) dynamic, 2) unpredictable and 3) incidental generally triggered by 1) professional issues shared by experts, 2) minority and less popular issues shared by popular opinion leaders, and 3) hot and important issues around the world. This study first tried to provide empirical evidence on daily tweets and investigated the learning taken place naturally among tweeters’ interactions. The results show that the learning on Twitter is different from the traditional learning that we used to know, and conclude the novel learning features mentioned above in the Information age. It is recommended for the future researchers to probe into tweets mentioned hashtags that relate to popular and well-known theme-based topics to see whether a different form of learning will be triggered.