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Language-Independent Fake News Detection: English, Portuguese, and Spanish Mutual Features
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In: Future Internet ; Volume 12 ; Issue 5 (2020)
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L'information dans la correspondance des représentants diplomatiques français pendant la crise austro-prussienne de 1866: Analyse des données textuelles d'un corpus de dépêches ...
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L'information dans la correspondance des représentants diplomatiques français pendant la crise austro-prussienne de 1866: Analyse des données textuelles d'un corpus de dépêches ...
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Native language identification of fluent and advanced non-native writers
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In: 19 ; 4 ; 1 (2020)
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Clips Stylometry Investigation (CSI) Corpus: A Dutch Corpus for the Detection of Age
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In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1_Paper.pdf (2014)
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Abstract:
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, topic 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%.
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Keyword:
computational stylometry; deception detection; text classification
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.680.5307
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1_Paper.pdf
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Following the Trail of Source Languages in Literary Translations ; Research and Development in Intelligent Systems XXXI
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Towards the automatic detection of the source language of a literary translation ; The 24th International Conference on Computational Linguistics (COLING2012)
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CLiPS Stylometry Investigation (CSI) corpus: A Dutch corpus for the detection of age, gender, personality, sentiment and deception in text
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In: http://www.cnts.ua.ac.be/sites/default/files/paper.csi_.lrec_.1.0.0.bv_.2014-03-21.final_.pdf
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