Tweeting Europe: A text-analytic approach to unveiling the content of political actors' Twitter activities in the European Parliament

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Title: Tweeting Europe: A text-analytic approach to unveiling the content of political actors' Twitter activities in the European Parliament
Authors: Cross, James P.
Greene, Derek
Belford, Mark
Permanent link: http://hdl.handle.net/10197/7805
Date: 25-Jun-2016
Abstract: Twitter is an important platform for communication and is frequently used by Members of the European Parliament (MEPs) to campaign and en- gage in discussion with constituents and colleagues in the parliament. Ex- amining the issues that MEPs talk about on Twitter can thus inform us about their political priorities. Topic modelling aims to summarise a corpus of documents by capturing the underlying hidden structure of the data and pre- senting the user with an overview of the key subjects and themes discussed in the corpus, known as topics. This paper aims to quantify and explore the content that MEPs pay attention to on Twitter by applying a new en- semble approach for topic modelling which involves applying two layers of Non-Negative Matrix Factorisation (NMF). The resulting set of issues paid attention to by MEPs are explained by considering the effects of events, is- sue characteristics, and MEP characteristics.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: Machine learning;Statistics
Language: en
Status of Item: Peer reviewed
Conference Details: 6th Annual General Conference of the European Political Science Association (EPSA'16), Brussels, Belgium, 23-25 June 2016
Appears in Collections:Politics and International Relations Research Collection
Computer Science Research Collection
Insight Research Collection

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