Foundation of Data, Data Warehousing, Data Mining and E Governance

Agarwal, Sonali; Tiwari, Murli Dhar; Tiwari, Iti

doi:10.1201/9781003357254-2

Cited by 1 publication

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“…Resolving a problem like this is very difficult because of the irregularity in the context of the words, phrases or clauses used in these comments (Ibrohim & Budi, 2019) [5] . Machine Learning is the conjunction of the statistical theorems and artificial intelligence techniques which tend to make computer program capable of learning from an observational data in deduction of an insightful pattern which could be used to making decisions of the intended goals (Agarwal, 2013) [1] . Sentiment analysis is one of the applications of Natural Language Processing (NLP), which deals with the motive behind human languages or expression whether written or oral.…”

Section: Introductionmentioning

confidence: 99%

A dataset of abusive comments on the Nigerian web

Oladipo,

Afolabi,

Ariwa

2021

Int. J. Comput. Artif. Intell.

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As the online comments keep growing in an exponential manner, the need for effective filtering or detecting abusive language in generated web textual content becomes increasingly important. In addition, the geometric increase in the textual content of the web has made the use of methods like word-bag and pattern matching for detection of hate speech less effective. The purpose of this work is to develop a corpus of online users' comments annotated for abusive language and develop a classification machine learning based model to detect hate speech on the Nigerian web. The model is evaluated on real-time comments and in different settings to further increase the learning rate of our model.

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Section: Introductionmentioning

confidence: 99%