Textual content based information retrieval from Twitter
Waseem Ahmad, Rashid Ali · 2016
Now a day's micro-blogging site Twitter1is rapidly gaining popularity among politician, celebrities, businessmen, academician and even ordinary people. Many users want to collect useful information from Twitter for possible future use. In this regard, the user requires a system that facilitates user to restore tweets and find them again with higher degree of relevance with user's query. In this paper, we propose a framework for tweets retrieval from Twitter. The system acquires information from Twitter by using Twitter search API and develops a corpus of user's contents by removing noisy and ambiguous elements from the retrieved collection of tweets. Further, we pose queries to obtain the results of the system. We find that the system return useful documents to the user in order of their decreasing relevance scores.