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Mentioning the Optimal Users in the Appropriate Time on Twitter.

, , , , , , and . APWeb (2), volume 9932 of Lecture Notes in Computer Science, page 464-468. Springer, (2016)

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Finding Influential Users and Popular Contents on Twitter., , , , , and . WISE (2), volume 9419 of Lecture Notes in Computer Science, page 267-275. Springer, (2015)Mentioning the Optimal Users in the Appropriate Time on Twitter., , , , , , and . APWeb (2), volume 9932 of Lecture Notes in Computer Science, page 464-468. Springer, (2016)Finding the Optimal Users to Mention in the Appropriate Time on Twitter., , , , and . KSEM, volume 9983 of Lecture Notes in Computer Science, page 289-301. (2016)Correlation and Visualization Analysis of Large Scale Dataset GDELT., and . IIKI, page 68-72. IEEE Computer Society, (2016)User-Guided Large Attributed Graph Clustering with Multiple Sparse Annotations., , , , , and . PAKDD (1), volume 9651 of Lecture Notes in Computer Science, page 127-138. Springer, (2016)Correlation Analysis Using Global Dataset of Events, Location and Tone., , and . DSC, page 648-652. IEEE Computer Society, (2016)Predicting Protest Events with Hidden Markov Models., and . CyberC, page 109-114. IEEE, (2016)An Online Framework for Temporal Social Unrest Event Prediction Using News Stream., , and . CyberC, page 176-182. IEEE, (2020)An Overview of Event Extraction from Twitter., , , , and . CyberC, page 251-256. IEEE Computer Society, (2015)Computational Approach to Detecting and Predicting Occupy Protest Events., and . IIKI, page 94-97. IEEE Computer Society, (2015)