Classification of news-related tweets

Abstract

It is important to obtain public opinion about a news article. Microblogs such as Twitter are popular and an important medium for people to share ideas. An important portion of tweets are related to news or events. Our aim is to find tweets about newspaper reports and measure the popularity of these reports on Twitter. However, it is a challenging task to match informal and very short tweets with formal news reports. In this study, we formulate this problem as a supervised classification task. We propose to form a training set using tweets containing a link to the news and the content of the same news article. We preprocess tweets by removing unnecessary words and symbols and apply stemming by means of morphological analysers. We apply binary classifiers and anomaly detection to this task. We also propose a textual similarity-based approach. We observed that preprocessing of tweets increases accuracy. The textual similarity method obtains results with the highest recognition rate. Success increases in some cases when report text is used with tweets containing a link to the news report within the training set of classification studies. We propose that this study, which is made directly in consideration of tweet texts that measure the trends of national newspaper reports on social media, has a higher significance when compared to Twitter analyses made by using a hashtag. Given the limited number of scientific studies on Turkish tweets, this study makes a contribution to the literature.

Time-aware domain-based social influence prediction

“…Demirsoz et al proposed a textual similarity-based approach for classifying national news reports tweets, and showed that it has a higher significance than Twitter analyses via a hashtag [46].…”

Online news media website ranking using user-generated content

“…In Krestel et al [80], the authors used 16 Twitter features such as publication time, length and follower count plus the similarity scores of tweets and news articles to find the most relevant tweets to each news article. Connecting news articles to Twitter conversations has also been studied in previous works [81–83]. For instance, in the framework proposed by Shi et al [81], the tweets are separated per article based on keyword similarity.…”

Feasibility of using social media to monitor outdoor air pollution in London, England

“…Therefore, we removed any tweets that referenced media sources by removing all tweets containing a URL link from our analysis. Previous studies have shown that tweets containing URL links are typically tweets that users post to share a news article or blog post (Demirsoz and Ozcan, 2017;Sankaranarayanan et al, 2009).…”