Finding question-answer pairs from online forums
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Predicting tie strength with social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A classification-based approach to question answering in discussion boards
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
An analysis of user influence ranking algorithms on Dark Web forums
ACM SIGKDD Workshop on Intelligence and Security Informatics
Classifying sentences as speech acts in message board posts
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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As criminals and terrorist employ social media platforms for planning and executing nefarious activities, understanding the degree of trustworthiness in interactions among actors becomes crucial for detecting their activities. Measuring trust in these environments can benefit analysts who are monitoring web forums to detect criminal or terrorist activities. Previous research proposed a trust model that could enable automatic trust discovery using speech act theory. This paper introduces a new classification method that enriches traditional techniques with contextual information. We conducted experiments to compare the proposed method with traditional approaches. The results show that the proposed method outperforms other alternative methods.