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Its All in a Name: Detecting and Labeling Bots by Their Name
Automated social media bots have existed almost as long as the social me...
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Identifying Compromised Accounts on Social Media Using Statistical Text Analysis
Compromised social media accounts are legitimate user accounts that have...
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Geovisual Analytics and Interactive Machine Learning for Situational Awareness
The first responder community has traditionally relied on calls from the...
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EQSA: Earthquake Situational Analytics from Social Media
This paper introduces EQSA, an interactive exploratory tool for earthqua...
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How Twitter Data Sampling Biases U.S. Voter Behavior Characterizations
Online social media are key platforms for the public to discuss politica...
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Using LDA and LSTM Models to Study Public Opinions and Critical Groups Towards Congestion Pricing in New York City through 2007 to 2019
This study explores how people view and respond to the proposals of NYC ...
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Requirements Intelligence with OpenReq Analytics
With the rise of social media like Twitter and distribution platforms li...
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VASSL: A Visual Analytics Toolkit for Social Spambot Labeling
Social media platforms such as Twitter are filled with social spambots. Detecting these malicious accounts is essential, yet challenging, as they continually evolve and evade traditional detection techniques. In this work, we propose VASSL, a visual analytics system that assists in the process of detecting and labeling spambots. Our tool enhances the performance and scalability of manual labeling by providing multiple connected views and utilizing dimensionality reduction, sentiment analysis and topic modeling techniques, which offer new insights that enable the identification of spambots. The system allows users to select and analyze groups of accounts in an interactive manner, which enables the detection of spambots that may not be identified when examined individually. We conducted a user study to objectively evaluate the performance of VASSL users, as well as capturing subjective opinions about the usefulness and the ease of use of the tool.
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