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Leveraging Natural Language Processing to Mine Issues on Twitter During the COVID-19 Pandemic
The recent global outbreak of the coronavirus disease (COVID-19) has spr...
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Automated Analysis of Topic-Actor Networks on Twitter: New approach to the analysis of socio-semantic networks
Social-media data provides increasing opportunities for automated analys...
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Mining Twitter to Assess the Determinants of Health Behavior towards Human Papillomavirus Vaccination in the United States
Objectives To test the feasibility of using Twitter data to assess deter...
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Recruitment Market Trend Analysis with Sequential Latent Variable Models
Recruitment market analysis provides valuable understanding of industry-...
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Optimizing Search API Queries for Twitter Topic Classifiers Using a Maximum Set Coverage Approach
Twitter has grown to become an important platform to access immediate in...
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Hashtags are (not) judgemental: The untold story of Lok Sabha elections 2019
Hashtags in online social media have become a way for users to build com...
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TrollHunter2020: Real-Time Detection of Trolling Narratives on Twitter During the 2020 US Elections
This paper presents TrollHunter2020, a real-time detection mechanism we ...
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A Comprehensive Analysis of Twitter Trending Topics
Twitter is among the most used microblogging and online social networking services. In Twitter, a name, phrase, or topic that is mentioned at a greater rate than others is called a "trending topic" or simply "trend". Twitter trends has shown their powerful ability in many public events, elections and market changes. Nevertheless, there has been very few works focusing on understanding the dynamics of these trending topics. In this article, we thoroughly examined the Twitter's trending topics of 2018. To this end, we accessed Twitter's trends API for the full year of 2018 and devised six criteria to analyze our dataset. These six criteria are: lexical analysis, time to reach, trend reoccurrence, trending time, tweets count, and language analysis. In addition to providing general statistics and top trending topics regarding each criterion, we computed several distributions that explain this bulk of data.
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