Paggamit ng natural language processing bilang gabay sa pagtuklas at pagsiyasat ng tema sa mga tweet tuwing halalan

Social Networking Sites or SNS are considered as gold mines of data, and one famous SNS is Twitter. It gives users a venue to express their feelings and thoughts on things; these include personal experiences, political topics, cultural events, etc. SNS increasingly are becoming famous mediums for communication especially during the time of election. However, manual analyses of tweets are time-consuming. In this study, we propose the use of natural language processing or NLP as guide in the discovery and analysis of themes in tweets concerning one particular topic: the election. Using automatic means, it reduces the amount of time needed to look for emerging themes. As testbed, we focused on the general midterm election of May 2013. In this study, we [1] collected 19,821 tweets from May 01 to 14 using a computer program; [2] generated topic models using the Stanford Modeling toolkit and proposed themes; [3] generated language models using the Stanford Research Institute Language Modeling toolkit; and [4] provided additional insights on the themes using the language models as guide. Themes can be categorized into nine: [1] experience after voting; [2] question and explanations; [3] encouragement and campaign; [4] names of candidates; [5] voting process; [6] humor; [7] fantasies; [8] organizations; and [9] criticisms on physical appearance. Further analysis, for instance with the use of discourse and content analysis, could be done by analyzing the socio-cultural aspect of the tweets.