Determining the Function of Political Tweets

Erik Tjong Kim Sang*, Herbert Kruitbosch, Marcel Broersma, Marc Esteve Del Valle

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)
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    Abstract

    We study the discursive practices of politicians and journalists on social media. For this we need more annotated data than we currently have but the annotation process is time-consuming and costly. In this paper we examine machine learning methods for automatically annotating unseen tweetsbased on a small set of manually annotated tweets. Forimproving the performance of the learner, we focus onmethods related to training data expansion, like artificialtraining data, active learning and incorporating languagemodels developed from unannotated text.

    Original languageEnglish
    Title of host publicationProceedings - 13th IEEE International Conference on eScience, eScience 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages438-439
    Number of pages2
    ISBN (Electronic)9781538626863
    DOIs
    Publication statusPublished - 14-Nov-2017
    Event13th IEEE International Conference on eScience, eScience 2017 - Auckland, New Zealand
    Duration: 24-Oct-201727-Oct-2017

    Conference

    Conference13th IEEE International Conference on eScience, eScience 2017
    CountryNew Zealand
    CityAuckland
    Period24/10/201727/10/2017

    Keywords

    • machine learning
    • political science
    • social media
    • Twitter

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