big data and cognitive computing Article Twitter Analyzer—How to Use Semantic Analysis to Retrieve an Atmospheric Image around Political Topics in Twitter Stefan Spettel 1 and Dimitrios Vagianos 2,* 1 Faculty of Informatics, Technical University of Vienna, Karlsplatz 13, 1040 Wien, Austria 2 Department of International and European Studies, University of Macedonia, Egnatia 156, 54636 Thessaloniki, Greece * Correspondence:
[email protected]; Tel.: +30-2310-891-487; Fax: +30-2310-891-285 Received: 5 June 2019; Accepted: 2 July 2019; Published: 6 July 2019 Abstract: Social media are heavily used to shape political discussions. Thus, it is valuable for corporations and political parties to be able to analyze the content of those discussions. This is exemplified by the work of Cambridge Analytica, in support of the 2016 presidential campaign of Donald Trump. One of the most straightforward metrics is the sentiment of a message, whether it is considered as positive or negative. There are many commercial and/or closed-source tools available which make it possible to analyze social media data, including sentiment analysis (SA). However, to our knowledge, not many publicly available tools have been developed that allow for analyzing social media data and help researchers around the world to enter this quickly expanding field of study. In this paper, we provide a thorough description of implementing a tool that can be used for performing sentiment analysis on tweets. In an effort to underline the necessity for open tools and additional monitoring on the Twittersphere, we propose an implementation model based exclusively on publicly available open-source software. The resulting tool is capable of downloading Tweets in real-time based on hashtags or account names and stores the sentiment for replies to specific tweets.