Kim D. Gorro, M. J. Sabellano, Ken Gorro, C. Maderazo, Kris Capao
{"title":"基于硒和SVM的Facebook网络欺凌分类","authors":"Kim D. Gorro, M. J. Sabellano, Ken Gorro, C. Maderazo, Kris Capao","doi":"10.1109/CCOMS.2018.8463326","DOIUrl":null,"url":null,"abstract":"Cyberbullying is one of the emerging problems over the past few years especially to teenagers. Approximately 24% of teens goes online constantly, facilitated by the widespread availability of smartphones. Almost 21% of teens said the main reason they checked social media always was to make sure nobody was saying mean or bad things to them. Cyberbullying related Facebook posts were harvested by a customized web scraper tool. These harvested data were used for classification using Support Vector Machines (SVM) model. A total of 2263 data was used for training data, Facebook posts. Based on these posts, the study achieved the precision of 88% and the recall is 87%.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"446 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Classification of Cyberbullying in Facebook Using Selenium and SVM\",\"authors\":\"Kim D. Gorro, M. J. Sabellano, Ken Gorro, C. Maderazo, Kris Capao\",\"doi\":\"10.1109/CCOMS.2018.8463326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cyberbullying is one of the emerging problems over the past few years especially to teenagers. Approximately 24% of teens goes online constantly, facilitated by the widespread availability of smartphones. Almost 21% of teens said the main reason they checked social media always was to make sure nobody was saying mean or bad things to them. Cyberbullying related Facebook posts were harvested by a customized web scraper tool. These harvested data were used for classification using Support Vector Machines (SVM) model. A total of 2263 data was used for training data, Facebook posts. Based on these posts, the study achieved the precision of 88% and the recall is 87%.\",\"PeriodicalId\":405664,\"journal\":{\"name\":\"2018 3rd International Conference on Computer and Communication Systems (ICCCS)\",\"volume\":\"446 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 3rd International Conference on Computer and Communication Systems (ICCCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCOMS.2018.8463326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCOMS.2018.8463326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of Cyberbullying in Facebook Using Selenium and SVM
Cyberbullying is one of the emerging problems over the past few years especially to teenagers. Approximately 24% of teens goes online constantly, facilitated by the widespread availability of smartphones. Almost 21% of teens said the main reason they checked social media always was to make sure nobody was saying mean or bad things to them. Cyberbullying related Facebook posts were harvested by a customized web scraper tool. These harvested data were used for classification using Support Vector Machines (SVM) model. A total of 2263 data was used for training data, Facebook posts. Based on these posts, the study achieved the precision of 88% and the recall is 87%.