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Author Profiling Using Semantic and Syntactic Features: Notebook for PAN at CLEF 2019
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. MTA-SZTE Research Group on Artificial Intelligence, Szeged, Hungary.ORCID iD: 0000-0002-0546-116x
Institute of Informatics, University of Szeged, Szeged, Hungary.
MindGarage, Kaiserslautern, Germany.
MindGarage, Kaiserslautern, Germany.
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2019 (English)In: CLEF 2019 Working Notes: Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum / [ed] Linda Cappellato, Nicola Ferro, David E. Losada, Henning Müller, RWTH Aachen University , 2019, article id 244Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present an approach for the PAN 2019 Author Profiling challenge. The task here is to detect Twitter bots and also to classify the gender of human Twitter users as male or female, based on a hundred select tweets from their profile. Focusing on feature engineering, we explore the semantic categories present in tweets. We combine these semantic features with part of speech tags and other stylistic features – e.g. character floodings and the use of capital letters – for our eventual feature set. We have experimented with different machine learning techniques, including ensemble techniques, and found AdaBoost to be the most successful (attaining an F1-score of 0.99 on the development set). Using this technique, we achieved an accuracy score of 89.17% for English language tweets in the bot detection subtask

Place, publisher, year, edition, pages
RWTH Aachen University , 2019. article id 244
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 2380
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-76936Scopus ID: 2-s2.0-85070487977OAI: oai:DiVA.org:ltu-76936DiVA, id: diva2:1373972
Conference
10th CLEF Conference and Labs of the Evaluation Forum (CLEF 2019), 9-12 September, 2019, Lugano, Switzerland
Available from: 2019-11-28 Created: 2019-11-28 Last updated: 2022-10-31Bibliographically approved

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Kovács, GyörgyAlonso, PedroLiwicki, Marcus

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