Social media information credibility-英文作业代写－r51due

英国essay论文精选范文：“Social media information credibility”，这篇论文讨论了社交媒体信息的可信度。随着互联网技术和移动技术的突飞猛进，社交媒体盛行。然而，在这丰富的媒体信息的背后，隐藏着漫天飞舞的谣言、病毒般传播的虚假照片和视频，这给人们幸福的生活、社会的稳定带来了严重的隐患。为了遏制虚假不良信息传播，营造健康向上的网络环境，信息可信度评估就成了迫在眉睫的问题。社交媒体信息可信度评估研究不仅有助于发展与完善网络信息资源管理理论，而且有助于提高社交媒体舆情监控、社交媒体搜索、社会化推荐等方面的效果。

With the Internet and mobile technology by leaps and bounds, the prevalence of social media, everyone can do the information producers, manufacturing information is extremely rich. However, behind this rich information, hidden rumors filled the sky, the virus spread of false photos and video, which gives people a happy life, social stability has brought serious risks. In order to curb the spread of false information, to create a healthy network environment, information credibility assessment has become an urgent problem, social media information in urgent need of "appraisers" and "polygraph.

Social media information credibility assessment research has a high academic value, but also has strong application value. Specifically, the academic value of social media information in the study of credibility assessment and to explore the false information generation mechanism, mode of communication, governance measures, is the social media environment, network information resource management theory of rich, development and improvement. Application of value in the study of social media information credibility assessment to help social media users to determine the credibility of information to create a healthy and healthy Internet environment, but also help to improve the social media information public opinion monitoring, social media information, social media search , Socialization and other aspects of the recommendation.

Social Media is a kind of media that supports users to create and exchange content through Web2.0 technology, such as Twitter, Facebook, Youtube, LinkedIn, Wiki, microblog, micro message, QQ, forum, Renren.com . Since 1973, Lipkin, Szpakowski and Felsenstein 3 people in the United States, California, Berkeley, the world's first public electronic bulletin board system, Community Memory, BBS and the early community of social media began to greet people. "Global social media, digital and mobile services by 2015 digital statistics trends" report shows: the global social media active users account for about 29% of the global population.

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Related research of social media from the 20th century, began in the 1980s, in about 2005 began to enter the stage of rapid development, the volume has increased year by year trend. In international journals, social media papers published more to be "Computers in Human Behavior". The past two years, the international conference on social media are ASONAM, SMP, MISNC, SMAP, SCSM. Foreign scholars mainly focus on the following four aspects:

Social media in the commercial field, education, public management and so has a wide range of applications. Such as marketing, social media information, consumer attitudes and behavior can be informed, customers can learn about the impact of communication and recommendation on marketing, you can learn the social media information on marketing management function.

Focusing on the social media information retrieval and information recommendation method research. The retrieval methods of social media information include theme model, social network and ontology. For example, Hong and Davison use the standard thematic model for social media Twitter information retrieval. The recommendations of social media information include content recommendation, collaborative filtering, timing recommendation, location recommendation and socialization recommendation. For example, Levandoski et al. proposed a location-aware recommendation system.

Focusing on the dissemination of information dissemination and dissemination of social media information model and the construction of the model through the construction of practical problems such as prediction of research. For example, Galuba et al. proposed a linear threshold model based on content popularity, user influence and propagation speed by studying the 300-hour spread of 15 million URLs between different Twitter users. Adar and Adamic proposed an epidemiological model to describe the mechanism of information transmission by studying the patterns and dynamics of information dissemination in blogs. Asur and Huberman used simple linear regression models to predict movie box office revenue using chat data from Twitter.com.

Based on the existing problems of privacy of social media users, the corresponding privacy protection methods are put forward. For example, Viswanath et al. first studied the shortcomings of Sybil defense and discussed the alternative method of Sybil defense. Conti et al. use FaceVPSN to solve social media user privacy issues.

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