Risul Islam Rasel, N. Sultana, Sharna Akhter, P. Meesad
{"title":"Detection of Cyber-Aggressive Comments on Social Media Networks: A Machine Learning and Text mining approach","authors":"Risul Islam Rasel, N. Sultana, Sharna Akhter, P. Meesad","doi":"10.1145/3278293.3278303","DOIUrl":"https://doi.org/10.1145/3278293.3278303","url":null,"abstract":"The spread of aggressive tweets, status and comments on social network are increasing gradually. People are using social media networks as a virtual platform to troll, objurgate, blaspheme and revile one another. These activities are spreading animosity in race-to-race, religion to religion etc. So, these comments should be identified and blocked on social networks. This work focuses on extracting comments from social networks and analyzes those comments whether they convey any blaspheme or revile in meaning. Comments are classified into three distinct classes; offensive, hate speech and neither. Document similarity analyses are done to identify the correlations among the documents. A well defined text pre-processing analysis is done to create an optimized word vector to train the classification model. Finally, the proposed model categorizes the comments into their respective classes with more than 93% accuracy.","PeriodicalId":183745,"journal":{"name":"Proceedings of the 2nd International Conference on Natural Language Processing and Information Retrieval","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126795958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The WebEngine: A Fully Integrated, Decentralised Web Search Engine","authors":"M. Kubek, H. Unger","doi":"10.1145/3278293.3278294","DOIUrl":"https://doi.org/10.1145/3278293.3278294","url":null,"abstract":"This paper presents a basic, new concept for decentralized web search which addresses major shortcomings of current web search engines. Its methods are characterised by their local working principles, making it possible to employ them on diverse hardware configurations. The concept's implementation in form of an interactive, librarian-inspired peer-to-peer software client, called 'WebEngine', is elaborated on in detail. This software extends and interconnects common web servers creating and forming a decentralised web search system on top of the existing web structure while --for the first time-- combining modern text analysis techniques with novel and efficient search functions as well as approaches for the semantically induced P2P-network construction and its exible management. This way, an alternative, fully integrated and powerful web search engine under the motto 'The Web is its own search engine.' is built making the web searchable without any central authority.","PeriodicalId":183745,"journal":{"name":"Proceedings of the 2nd International Conference on Natural Language Processing and Information Retrieval","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122567530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improving Named Entity Recognition of English and Vietnamese Languages using Bilingual Constraints","authors":"Thinh Truong, A. Dao, Long H. B. Nguyen, D. Dinh","doi":"10.1145/3278293.3278305","DOIUrl":"https://doi.org/10.1145/3278293.3278305","url":null,"abstract":"Named entity recognition plays a crucial role in many Natural Language Processing tasks because the semantic information is carried by entities. The recent efforts are trying to reduce the annotation labor because the state-of-the-art Named Entity Recognition systems are still based on supervised machine learning algorithms that require huge amounts of training data. Such training data are difficult and expensive to produce manually. In particular, Vietnamese is a resource-limited language which lacks high-quality named entity annotated corpora. This limitation leads to the low performance of Vietnamese Named Entity Recognition. Therefore, in this paper, thanks to the use of an existing unannotated English-Vietnamese bilingual corpus, we propose an approach to improve Named Entity Recognition systems of both English and Vietnamese languages. Experimental results show an improvement of both English and Vietnamese Named Entity Recognition compared to the strong baseline StanfordNER. In particular, Vietnamese Named Entity Recognition improves significantly by 18.45% in term of F1-score. As for the English side, F1-score improves from 92.44% to 95.05%. Our proposed method can also be generalized to apply to other resource-limited languages.","PeriodicalId":183745,"journal":{"name":"Proceedings of the 2nd International Conference on Natural Language Processing and Information Retrieval","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131764506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 2nd International Conference on Natural Language Processing and Information Retrieval","authors":"","doi":"10.1145/3278293","DOIUrl":"https://doi.org/10.1145/3278293","url":null,"abstract":"","PeriodicalId":183745,"journal":{"name":"Proceedings of the 2nd International Conference on Natural Language Processing and Information Retrieval","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128518666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}