Twitter as a Tool for Predicting Elections Results
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Learning from the crowd: an evolutionary mutual reinforcement model for analyzing events
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
| Hi-index | 0.00 |
Social media platforms have become a forum for giving a voice to the masses with a significant proportion of those masses coming from the developing world. This was largely evidenced through the significant role played by social media platforms in the recent uprisings in the Arab world. In this paper, we take up a study of social media engagement patterns of users from the developing world through a study of Twitter's role during the recent Tunisian uprising. Motivated by the results of a user survey conducted mainly for users from the developing world who tweeted heavily during the uprisings in the Arab world, we propose a novel method for subjectivity analysis of tweets corresponding to political events in the developing world. Our proposed method differs from previous subjectivity analysis approaches in that it is the first method that takes into account social features of social media platforms for the subjectivity classification task. Through experimental evaluations, we observe the accuracy of the proposed method to be 83.3% which demonstrates a promising outcome for large-scale application of our proposed subjectivity analysis technique.