This tool allows users to build a vocabulary from a twitter query by returning co-occurring words based on frequency and significance.
Nabeel Abdur Rehman [[email protected], nar397]
Hovsep Agop [[email protected], hka245]
With the introduction of social media networks like Twitter and Facebook, there has been a growing interest in the analysis of social media data to answer questions in a wide range of domains. The first step in such studies requires researchers and analysts to download twitter data for the problem on hand, however defining keywords associated with the problem on hand is not a straightforward task. The goal of this tool is to help researchers and analysts to generate a vocabulary of all the keywords that can potentially be related to the problem on hand by providing intelligent suggestions based on live twitter stream and their already provided keyword terms. Additionally, the suggestions provided by the system are dependent on time. To achieve this goal, our system filters through a high volume of live and old tweets to offers suggestions for word inclusion based on term frequency and significance. Additionally, the user is able to narrow their search to tweets in the last 2 months, 1 month, 2 weeks, 1 week, and 3 days. The primary audience for this tool is researchers and analysts.
