Title: Credibility Analysis for Tweets Written in Turkish by a Hybrid Method

Year of Publication: Jul - 2016
Page Numbers: 55-62
Authors: Ali Fatih Gündüz, Pinar Karagöz
Conference Name: The Third International Conference on Data Mining, Internet Computing, and Big Data (BigData2016)
- Turkey

Abstract:


In this work, we have studied credibility analysis of microblogging. We collected our data from one of the most important microblogging services, Twitter. Our data set is created from the Turkish tweets written for weekly television programs broadcast in Turkey with political, cultural or financial contents. We adapted a new credibility definition based on three dimensions: being free from offensive words, not being spam and being newsworthy. To analyse credibility of tweets we proposed a method by hybridizing content based techniques with collaborative filtering techniques. The proposed method consists of two phases: supervised learning and graph based improvement. Classification algorithms are applied in the supervised learning phase and results are improved in the graph based phase of the method. We focused on tweet-tweet, tweet-writer and writer-writer relations in the second phase of our study.