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SAMSN 2021 : The International Workshop on Sentiment Analysis and Mining of Social Networks

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Link: http://emergingtechnet.org/SAMSN2021/
 
When Dec 6, 2021 - Dec 9, 2021
Where Gandia, Spain
Submission Deadline Oct 20, 2021
Notification Due Oct 31, 2021
Final Version Due Nov 10, 2021
Categories    social networks analysis   mining of social networks   sentiment analysis   machine learning
 

Call For Papers

When the first Social Networks were introduced in the beginning of this century, they were able to gain the attention of the whole world, and since then, more and more social networks have risen and have become increasingly popular and significantly effective. They have been able to change the way we live forever and how we interact with each other and with the environment. The world has become more and more connected. Nowadays, social networks are everywhere, and they play an important role in various aspects of our lives. With the rise of the era of social networks, many opportunities and challenges have appeared on the scene including but not limited to big data handling, security and privacy issues in social networks, the use of sentiment analysis and opinion mining in these rich environments, data analytics, recommender systems, and legal and ethical issues related to the offensive use of these environments. The objective of this workshop is to shed light upon all the issues, opportunities, challenges, and future trends that are related to online social networks. Authors are invited to submit their original work, which is not submitted elsewhere, to this workshop. The accepted papers of the workshop will be published by the IEEE Conference Publishing Services (CPS) and will be submitted for inclusion in the IEEE-Xplore and the IEEE Computer Society (CSDL) digital libraries.

The International Conference on Social Networks Analysis, Management and Security (SNAMS-2021) aims to provide a forum that brings together researchers, industry practitioners and domain experts for discussion and exchange of ideas on the latest theoretical developments in Data Science and Computing as well as on the best practices for a wide range of applications.

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