{"title":"网络上的真相技术","authors":"D. Bylieva","doi":"10.18254/s207751800024139-1","DOIUrl":null,"url":null,"abstract":"The spread of misinformation on the Internet today is a serious problem due to the vast impact on society of network information. The most obvious technology aimed at combating false information is fact-checking, which allows to identify the presence of facts in the message and compare them with the base of true information. Such technologies are applicable for tracking information distortions, but do not allow evaluating a random message. An alternative approach is to identify false messages based on indirect signs: its linguistic and paralinguistic features, as well as on the communicative history (author, creation and distribution) and other features. Database-trained artificial intelligence concludes that messages are false, without resorting to comparison with true judgments and logical procedures. The ability of a person to independently evaluate the truth of messages is limited by the economy of cognitive effort, and people are even able to generate their own memories that confirm false messages.","PeriodicalId":51498,"journal":{"name":"Jasss-The Journal of Artificial Societies and Social Simulation","volume":"25 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Technologies of truth on the web\",\"authors\":\"D. Bylieva\",\"doi\":\"10.18254/s207751800024139-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The spread of misinformation on the Internet today is a serious problem due to the vast impact on society of network information. The most obvious technology aimed at combating false information is fact-checking, which allows to identify the presence of facts in the message and compare them with the base of true information. Such technologies are applicable for tracking information distortions, but do not allow evaluating a random message. An alternative approach is to identify false messages based on indirect signs: its linguistic and paralinguistic features, as well as on the communicative history (author, creation and distribution) and other features. Database-trained artificial intelligence concludes that messages are false, without resorting to comparison with true judgments and logical procedures. The ability of a person to independently evaluate the truth of messages is limited by the economy of cognitive effort, and people are even able to generate their own memories that confirm false messages.\",\"PeriodicalId\":51498,\"journal\":{\"name\":\"Jasss-The Journal of Artificial Societies and Social Simulation\",\"volume\":\"25 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jasss-The Journal of Artificial Societies and Social Simulation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.18254/s207751800024139-1\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jasss-The Journal of Artificial Societies and Social Simulation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.18254/s207751800024139-1","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
The spread of misinformation on the Internet today is a serious problem due to the vast impact on society of network information. The most obvious technology aimed at combating false information is fact-checking, which allows to identify the presence of facts in the message and compare them with the base of true information. Such technologies are applicable for tracking information distortions, but do not allow evaluating a random message. An alternative approach is to identify false messages based on indirect signs: its linguistic and paralinguistic features, as well as on the communicative history (author, creation and distribution) and other features. Database-trained artificial intelligence concludes that messages are false, without resorting to comparison with true judgments and logical procedures. The ability of a person to independently evaluate the truth of messages is limited by the economy of cognitive effort, and people are even able to generate their own memories that confirm false messages.
期刊介绍:
The Journal of Artificial Societies and Social Simulation is an interdisciplinary journal for the exploration and understanding of social processes by means of computer simulation. Since its first issue in 1998, it has been a world-wide leading reference for readers interested in social simulation and the application of computer simulation in the social sciences. Original research papers and critical reviews on all aspects of social simulation and agent societies that fall within the journal"s objective to further the exploration and understanding of social processes by means of computer simulation are welcome.