Eric Ferreira dos Santos, Danilo S. Carvalho, Jonice Oliveira
{"title":"媒介素养中Bot信息的模式识别","authors":"Eric Ferreira dos Santos, Danilo S. Carvalho, Jonice Oliveira","doi":"10.1145/3470482.3479452","DOIUrl":null,"url":null,"abstract":"The massive use of online social media is a reality nowadays. Such an increasing usage also raises growth in malicious activities in social media, one of which is the use of automated users (bots) that disseminate false information and can insert bias in analyses done on gathered social media data. Based on the concept of media literacy, this research presents a method to teach the human user to identify a pattern of a text produced by a bot, providing a tool (guide) to analyze social media text. Users who learned to identify a bot user with the guide had an average of 90% accuracy in the classification of new messages, against 57% of the participants who had no contact with the guide. The produced guide received a usefulness rating between 4 and 5 by the participants (scale from 1 to 5, with 5 being the highest value).","PeriodicalId":350776,"journal":{"name":"Proceedings of the Brazilian Symposium on Multimedia and the Web","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pattern Identification of Bot Messages for Media Literacy\",\"authors\":\"Eric Ferreira dos Santos, Danilo S. Carvalho, Jonice Oliveira\",\"doi\":\"10.1145/3470482.3479452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The massive use of online social media is a reality nowadays. Such an increasing usage also raises growth in malicious activities in social media, one of which is the use of automated users (bots) that disseminate false information and can insert bias in analyses done on gathered social media data. Based on the concept of media literacy, this research presents a method to teach the human user to identify a pattern of a text produced by a bot, providing a tool (guide) to analyze social media text. Users who learned to identify a bot user with the guide had an average of 90% accuracy in the classification of new messages, against 57% of the participants who had no contact with the guide. The produced guide received a usefulness rating between 4 and 5 by the participants (scale from 1 to 5, with 5 being the highest value).\",\"PeriodicalId\":350776,\"journal\":{\"name\":\"Proceedings of the Brazilian Symposium on Multimedia and the Web\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Brazilian Symposium on Multimedia and the Web\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3470482.3479452\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Brazilian Symposium on Multimedia and the Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3470482.3479452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern Identification of Bot Messages for Media Literacy
The massive use of online social media is a reality nowadays. Such an increasing usage also raises growth in malicious activities in social media, one of which is the use of automated users (bots) that disseminate false information and can insert bias in analyses done on gathered social media data. Based on the concept of media literacy, this research presents a method to teach the human user to identify a pattern of a text produced by a bot, providing a tool (guide) to analyze social media text. Users who learned to identify a bot user with the guide had an average of 90% accuracy in the classification of new messages, against 57% of the participants who had no contact with the guide. The produced guide received a usefulness rating between 4 and 5 by the participants (scale from 1 to 5, with 5 being the highest value).