2017
DOI: 10.15439/2017f461
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Open Class Authorship Attribution of Lithuanian Internet Comments using One-Class Classifier

Abstract: Internet can be misused by cyber criminals as a platform to conduct illegitimate activities (such as harassment, cyber bullying, and incitement of hate or violence) anonymously. As a result, authorship analysis of anonymous texts in Internet (such as emails, forum comments) has attracted significant attention in the digital forensic and text mining communities. The main problem is a large number of possible of authors, which hinders the effective identification of a true author. We interpret open class author … Show more

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Cited by 15 publications
(7 citation statements)
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“…An open-set attribution of Lithuanian Internet Comments was discussed in [27]. The authors developed the recommendation system that returns a list of alleged authors and their corresponding probabilities for further analysis by experts.…”
Section: Related Work On Classical Machine Learning Methods and Deep Neural Network For Authorship Attributionmentioning
confidence: 99%
“…An open-set attribution of Lithuanian Internet Comments was discussed in [27]. The authors developed the recommendation system that returns a list of alleged authors and their corresponding probabilities for further analysis by experts.…”
Section: Related Work On Classical Machine Learning Methods and Deep Neural Network For Authorship Attributionmentioning
confidence: 99%
“…Kedua algoritma pilihan para peneliti tersebut sama terkenalnya dengan KNN. Akan tetapi beberapa penelitian menunjukkan akurasi KNN melebih neural networks [15]- [18]. Sedangkan untuk penelitian dengan algoritma buatan Panella belum ada perbandingan performanya.…”
Section: Pendahuluanunclassified
“…Natural language processing (NLP) is a field of research that deals with machine learning (ML) algorithms applied to human natural languages [5]. NLP applications aim to automatically process written and spoken human languages including sentiment analysis [6,7], sarcasm detection [8], machine translation [9], speech recognition [10], automated dialogue systems [11], urban studies [12,13], topic classification [14], similarity detection [15], text summarization [16], intent detection [17], news and social media analysis [18,19], part-of-speech (POS) tagging [20], authorship attribution [21,22], fake tweet detection [23], coreference resolution [24] and others [14,[25][26][27]. Recently, NLP techniques have also been employed to study the sentiments and attitudes of social media users regarding the COVID-19 pandemic [28,29].…”
Section: Introductionmentioning
confidence: 99%