Text Mining Applied to Lobbyism Research

  • This thesis aims to investigate the relationship between opinions of politicians expressed in speeches and politicians’ paid side-activities of politicians, a potential channel of influence for lobbyists. With a focus on methodology development to automatically extract opinions and opinion changes for a specific item on the political agenda, the thesis reveals insights hidden in political speeches. Advancements in text mining present new opportunities to design advanced algorithms to achieve the stated objective. Along the journey of developing the methodology, the richness of used and possible algorithm components is discussed.

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Metadaten
Author:Sebastian Seck
Referee:Markus Löcher
Advisor:Andreas Polk
Document Type:Master's Thesis
Language:English
Date of first Publication:2019/09/03
Publishing Institution:Hochschulbibliothek HWR Berlin
Granting Institution:Hochschule für Wirtschaft und Recht Berlin
Date of final exam:2018/01/24
Release Date:2019/09/03
Tag:Deutscher Bundestag; Lobbyism; Moonlighting; Natural Language Processing; Opinion Analysis; Text Mining
Page Number:166
Institutes:FB I - Wirtschaftswissenschaften / Business Intelligence and Process Management M.Sc.
Licence (German):License LogoUrheberrechtsschutz