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hate-alert@DravidianLangTech-ACL2022: Ensembling Multi-Modalities for Tamil TrollMeme Classification ...
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Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages ...
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A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification ...
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Hate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection ...
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5
When expertise gone missing: Uncovering the loss of prolific contributors in Wikipedia ...
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6
Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languages ...
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7
Deep Learning Models for Multilingual Hate Speech Detection ...
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Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection ...
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9
Thou Shalt Not Hate: Countering Online Hate Speech
In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 13 (2019): Thirteenth International AAAI Conference on Web and Social Media; 369-380 ; 2334-0770 ; 2162-3449 (2019)
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On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings ...
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11
StRE: Self Attentive Edit Quality Prediction in Wikipedia ...
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12
Deep Dive into Anonymity: A Large Scale Analysis of Quora Questions ...
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13
Detecting Reliable Novel Word Senses: A Network-Centric Approach ...
Abstract: In this era of Big Data, due to expeditious exchange of information on the web, words are being used to denote newer meanings, causing linguistic shift. With the recent availability of large amounts of digitized texts, an automated analysis of the evolution of language has become possible. Our study mainly focuses on improving the detection of new word senses. This paper presents a unique proposal based on network features to improve the precision of new word sense detection. For a candidate word where a new sense (birth) has been detected by comparing the sense clusters induced at two different time points, we further compare the network properties of the subgraphs induced from novel sense cluster across these two time points. Using the mean fractional change in edge density, structural similarity and average path length as features in an SVM classifier, manual evaluation gives precision values of 0.86 and 0.74 for the task of new sense detection, when tested on 2 distinct time-point pairs, in comparison to ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1812.05936
https://dx.doi.org/10.48550/arxiv.1812.05936
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14
CL Scholar: The ACL Anthology Knowledge Graph Miner ...
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15
Analyzing the hate and counter speech accounts on Twitter ...
Mathew, Binny; Kumar, Navish; Ravina. - : arXiv, 2018
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16
What Propels Celebrity Follower Counts? Language Use or Social Connectivity ...
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17
Understanding Psycholinguistic Behavior of predominant drunk texters in Social Media ...
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18
AppTechMiner: Mining Applications and Techniques from Scientific Articles ...
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19
Language Use Matters: Analysis of the Linguistic Structure of Question Texts Can Characterize Answerability in Quora ...
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20
Language Use Matters: Analysis of the Linguistic Structure of Question Texts Can Characterize Answerability in Quora
In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 11 No. 1 (2017): Eleventh International AAAI Conference on Web and Social Media ; 2334-0770 ; 2162-3449 (2017)
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