Effects of Social Networks and Machine Learning Problem Solving Applications in Societies Nowadays
A special issue of Societies (ISSN 2075-4698).
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 228
Special Issue Editors
2. Centre for Informatics and Systems of the University of Coimbra (CISUC), 3030-790 Coimbra, Portugal
Interests: social networks; machine learning; text classification; natural language processing; dynamic environments; crowdsourcing
Interests: social networks; machine learning; text classification; dynamic environments; crowdsourcing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The constant growth of social platforms such as Twitter and Facebook shows the importance of social media in people’s lives today. We are now all connected to friends, family, and communities all around the world, and share information on a daily basis. Although mostly considered as an entertainment tool, some networks can be an important source of information, since relevant and valuable information is publicly shared among users. This is one of the important achievements of our time—the rapid pace at which we can learn about and propagate events.
The applications of social networks in modern societies are endless, usually with the goal of providing a solution to a global or specific problem. Considering machine learning applications, one can mention event detection, information spreading, community mining, crowdsourcing and sentiment analysis, among others.
This Special Issue seeks to bring together a set of papers regarding how machine learning applied to social media can contribute to problem solving in societies. Researchers can find in this Special Issue a venue for presenting both theoretical and practical approaches allowing the presentation and discussion of innovative solutions by addressing a number of open challenges in the above-mentioned fields.
Dr. Joana Costa
Dr. Catarina Silva
Guest Editors
Manuscript Submission Information
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Keywords
- social networks
- machine learning
- text classification
- event detection
- information spreading
- community mining
- crowdsourcing
- sentiment analysis
- natural language processing
- big data
- pattern recognition
- dynamic environments
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