{"title":"Truther框架的开发前分析:一个信息真实性验证平台","authors":"Alfian Akbar Gozali","doi":"10.1109/ICRAMET51080.2020.9298635","DOIUrl":null,"url":null,"abstract":"Today, an enormous information stream rapidly floods from various channels and media, such as websites, blogs, WhatsApp, Facebook, etc. This condition makes us incapable of reading all the content, let alone verify the context. To overcome this fuzzy problem, we introduce Truther, a lightweight on-demand app and web browser plugin, to verify digital information. Truther can verify text and images from websites, blogs, WhatsApp, Facebook, and more. It is mainly based on text input, so the usage is very open to any possibility. Truther is backing up by three central back-end systems such as Truther Validator (the cross-language text semantic verifier for validating a post), Truther Debunker Aggregator (aggregator of many hoax-debunker websites), and third-party API (Google, DuckDuckGo, and Microsoft Cognitive Service API). This paper mainly discusses our proposed framework’s pre-development analysis, its cross-language text semantic verifier, and MVP experiment result. As an additional finding, we also formalize the proposed business model of Truther.","PeriodicalId":228482,"journal":{"name":"2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pre-Development Analysis of Truther Framework: A Platform to Verify Information Authenticity\",\"authors\":\"Alfian Akbar Gozali\",\"doi\":\"10.1109/ICRAMET51080.2020.9298635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today, an enormous information stream rapidly floods from various channels and media, such as websites, blogs, WhatsApp, Facebook, etc. This condition makes us incapable of reading all the content, let alone verify the context. To overcome this fuzzy problem, we introduce Truther, a lightweight on-demand app and web browser plugin, to verify digital information. Truther can verify text and images from websites, blogs, WhatsApp, Facebook, and more. It is mainly based on text input, so the usage is very open to any possibility. Truther is backing up by three central back-end systems such as Truther Validator (the cross-language text semantic verifier for validating a post), Truther Debunker Aggregator (aggregator of many hoax-debunker websites), and third-party API (Google, DuckDuckGo, and Microsoft Cognitive Service API). This paper mainly discusses our proposed framework’s pre-development analysis, its cross-language text semantic verifier, and MVP experiment result. As an additional finding, we also formalize the proposed business model of Truther.\",\"PeriodicalId\":228482,\"journal\":{\"name\":\"2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAMET51080.2020.9298635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAMET51080.2020.9298635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pre-Development Analysis of Truther Framework: A Platform to Verify Information Authenticity
Today, an enormous information stream rapidly floods from various channels and media, such as websites, blogs, WhatsApp, Facebook, etc. This condition makes us incapable of reading all the content, let alone verify the context. To overcome this fuzzy problem, we introduce Truther, a lightweight on-demand app and web browser plugin, to verify digital information. Truther can verify text and images from websites, blogs, WhatsApp, Facebook, and more. It is mainly based on text input, so the usage is very open to any possibility. Truther is backing up by three central back-end systems such as Truther Validator (the cross-language text semantic verifier for validating a post), Truther Debunker Aggregator (aggregator of many hoax-debunker websites), and third-party API (Google, DuckDuckGo, and Microsoft Cognitive Service API). This paper mainly discusses our proposed framework’s pre-development analysis, its cross-language text semantic verifier, and MVP experiment result. As an additional finding, we also formalize the proposed business model of Truther.