Social Networks are responsible of generating a huge amount of information, intrinsically heterogeneous and coming from different sources. In the social networks domain, the number of active users is impressive, active users process and publish information in different formats and data remain heterogeneous in their topics and in the published media (text, video, images, audio, etc.). In this work, we present a general framework for event detection in processing of heterogeneous data from social networks. The framework we propose, implements some techniques that users can exploit for malicious events detection on Twitter.

Textual Processing in Social Network Analysis

Moscato F.
2019

Abstract

Social Networks are responsible of generating a huge amount of information, intrinsically heterogeneous and coming from different sources. In the social networks domain, the number of active users is impressive, active users process and publish information in different formats and data remain heterogeneous in their topics and in the published media (text, video, images, audio, etc.). In this work, we present a general framework for event detection in processing of heterogeneous data from social networks. The framework we propose, implements some techniques that users can exploit for malicious events detection on Twitter.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4782529
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