{"title":"Extracting Emerging Topics Based on User Comments","authors":"J. Ms, T. Ms","doi":"10.20894/ijwt.104.008.001.007","DOIUrl":null,"url":null,"abstract":"The Social website is the place where people can share information about the current events around the world at any time. Social Network Data Analysis Applications have experienced tremendous improvements over the past few years. Due to its straightforwardness, this social network allows data trends to detect current trends, which will have the capacity to affect company global research on the common market research and group program. Unfortunately, by mistake, social network trends mislead people. Trend handling is based entirely on the users text post, including the text and its current combined searches and detection of current trends, but these methods do not know behind compromise and pseudo account users. Therefore, we try to design a safe dialogue approach for handling trends in social networking, which will have a real account of complex manufacturers and small business entities trying to reach fraudulent means and creates compromises and fake accounts. Users made us pay attention to this logic that will lead us to remove the current topic of interest between users to process these contents in this particular behavior.","PeriodicalId":39662,"journal":{"name":"International Journal of Web Engineering and Technology","volume":"23 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Web Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20894/ijwt.104.008.001.007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
The Social website is the place where people can share information about the current events around the world at any time. Social Network Data Analysis Applications have experienced tremendous improvements over the past few years. Due to its straightforwardness, this social network allows data trends to detect current trends, which will have the capacity to affect company global research on the common market research and group program. Unfortunately, by mistake, social network trends mislead people. Trend handling is based entirely on the users text post, including the text and its current combined searches and detection of current trends, but these methods do not know behind compromise and pseudo account users. Therefore, we try to design a safe dialogue approach for handling trends in social networking, which will have a real account of complex manufacturers and small business entities trying to reach fraudulent means and creates compromises and fake accounts. Users made us pay attention to this logic that will lead us to remove the current topic of interest between users to process these contents in this particular behavior.
期刊介绍:
The IJWET is a refereed international journal providing a forum and an authoritative source of information in the fields of web engineering and web technology. It is devoted to innovative research in the analysis, design, development, use, evaluation and teaching of web-based systems, applications, sites and technologies.