CLiPS Stylometry Investigation (CSI) Corpus: A Dutch corpus for the detection of age, gender, personality, sentiment and deception in text

TitleCLiPS Stylometry Investigation (CSI) Corpus: A Dutch corpus for the detection of age, gender, personality, sentiment and deception in text
Publication TypeConference Paper
Year of Publication2014
AuthorsVerhoeven, B, Daelemans, W
Conference NameProceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014)
PublisherEuropean Language Resources Association (ELRA)
Conference LocationReykjavik, Iceland
Abstract

Research in computational stylometry has always been constrained by the limited availability of training data since collecting textual data with the appropriate meta-data requires a large effort. We present the CLiPS Stylometry Investigation (CSI) corpus, a new Dutch corpus containing reviews and essays written by university students. It is designed to serve multiple purposes: detection of age, gender, authorship, personality, sentiment, deception and genre. Another major advantage is its planned yearly expansion with each year’s new students. The corpus currently contains about 305,000 tokens spread over 749 documents. The average review length is 128 tokens; the average essay length is 1126 tokens. The corpus will be made available on the CLiPS website (www.clips.uantwerpen.be/datasets) and can freely be used for academic research purposes.

An initial deception detection experiment was performed on this data. Deception detection is the task of automatically classifying a text as being either truthful or deceptive, in our case by examining the writing style of the author. This task has never been investigated for Dutch before. We performed a supervised machine learning experiment using the SVM algorithm in a 10-fold cross-validation setup. The only features were the token unigrams present in the training data. Using this simple method, we reached a state-of-the-art F-score of 72.2%.

File: