Call for Papers: Social Media Analytics and its Evaluation

Call for Papers: Social Media Analytics and its Evaluation

Submission deadline: August 31, 2020

Guest Editors: Thomas Mandl; Sandip Modha; Prasenjit Majumder

Social Media has become the most prominent forum for online expression. With ever more content being uploaded, the amount of questionable and problematic message is also rising. The online availability of aggressive and hateful text might have long-term negative effects on people’s opinions and social cohesion. As a consequence, the detection of Hate Speech and other problematic content has become a necessity for society. Much research is done by large companies, however, for social acceptance of such systems limiting the right of Free Speech a good understanding and publically available research is necessary. Several evaluation tracks have been organized in recent years and the best approaches for creating detection systems are being evaluated. Currently, modern deep learning technologies seem to be the superior method for the task. The evaluation of such algorithms for a variety of languages is a scientific challenge in itself. How can a test collection be assembled to achieve results which are applicable in realworld scenarios? The call for this special issue welcomes submissions on the optimization of algorithms for Hate Speech detection, analysis to better understand the performance of such systems and work reflecting the reliability of evaluation datasets.

This special issue aims to bring together the communities of Natural Language Processing, Information Retrieval, Information extraction, Text analytics and Machine learning to solve the challenges mentioned.

Topics: The special issue solicits the submission of high-quality research papers related to the theme, which includes (but is not limited to):

 • Online Hate Speech Detection

 • Offensive Language and Abusive Language Identification

 • Trolling and Cyber bullying in Social Media

 • Sentiment analysis on Social media data

 • Sarcasm Detection

 •Hate Speech Detection across Heterogeneous Culture

 • Research on Datasets for Hate Speech and Offensive Language Detection  

 • Corpus Creation for Hate Speech/Sentiment analysis

 • Evaluation of Content Moderation systems