An Introduction to Social Semantic Web Mining & Big Data Analytics for Political Attitudes and Mentalities Research

• Main Authors: Markus Schatten, Jurica Ševa, Bogdan Okreša Đurić
• Format: Article
• Language: English
• Published: University of Bucharest 2015-01-01
• Series: European Quarterly of Political Attitudes and Mentalities
• Subjects: : social semantic web; web mining; big data analytics; network theory; network visualization; agent based modeling; natural language processing; sentiment analysis
• Online Access: https://sites.google.com/a/fspub.unibuc.ro/european-quarterly-of-political-attitudes-and-mentalities/Home/eqpam-vol4-no1-january2015---markus-schatten-jurica-seva-bogdan-okresa-dhuric

The social web has become a major repository of social and behavioral data that is of exceptional interest to the social science and humanities research community. Computer science has only recently developed various technologies and techniques that allow for harvesting, organizing and analyzing such data and provide knowledge and insights into the structure and behavior or people on-line. Some of these techniques include social web mining, conceptual and social network analysis and modeling, tag clouds, topic maps, folksonomies, complex network visualizations, modeling of processes on networks, agent based models of social network emergence, speech recognition, computer vision, natural language processing, opinion mining and sentiment analysis, recommender systems, user profiling and semantic wikis. All of these techniques are briefly introduced, example studies are given and ideas as well as possible directions in the field of political attitudes and mentalities are given. In the end challenges for future studies are discussed.