TwitterCracy: Exploratory Monitoring of Twitter Streams for the 2016 U.S. Presidential Election Cycle
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|Title:||TwitterCracy: Exploratory Monitoring of Twitter Streams for the 2016 U.S. Presidential Election Cycle||Authors:||Qureshi, M. Atif
|Permanent link:||http://hdl.handle.net/10197/8367||Date:||23-Sep-2016||Abstract:||We present TwitterCracy, an exploratory search system that allows users to search and monitor across the Twitter streams of political entities. Its exploratory capabilities stem from the application of lightweight time-series based clustering together with biased PageRank to extract facets from tweets and presenting them in a manner that facilitates exploration.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Springer||Copyright (published version):||2016 Springer||Keywords:||Machine learning;Statistics||DOI:||10.1007/978-3-319-46131-1_16||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings, Part III: Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2016 (Volume 9853)||Conference Details:||European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD ’16), Riva del Garda, 19-23 September 2016|
|Appears in Collections:||Insight Research Collection|
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