Recently, there has been a radial shift from traditional online social networks to content-generated social networks(CGSNs). Contemporary CGSNs, such as Dianping and Trip Advisor, are often the targets of click farmin...Recently, there has been a radial shift from traditional online social networks to content-generated social networks(CGSNs). Contemporary CGSNs, such as Dianping and Trip Advisor, are often the targets of click farming in which fake reviews are posted in order to boost or diminish the ratings of listed products and services simply through clicking. Click farming often emanates from a collection of multiple fake or compromised accounts, which we call click farmers. In this paper, we conduct a three-phase methodology to detect click farming. We begin by clustering communities based on newly-defined collusion networks. We then apply the Louvain community detection method to detecting communities. We finally perform a binary classification on detected-communities. Our results of over a year-long study show that(1) the prevalence of click farming is different across CGSNs;(2) most click farmers are lowly-rated;(3) click-farming communities have relatively tight relations between users;(4) more highly-ranked stores have a greater portion of fake reviews.展开更多
With the rapid development of the Internet,more and more people begin to pay attention to social tagging which is a flexible and efficient method for classification. How to retrieve tags from the huge tag library beco...With the rapid development of the Internet,more and more people begin to pay attention to social tagging which is a flexible and efficient method for classification. How to retrieve tags from the huge tag library becomes a hot topic to research. Firstly,the existing systems of social tags and its recommendation principles used in Web 2. 0 are introduced in this paper. Secondly,the existing techniques about tag recommendation are summarized,and their merits and demerits are analysed. In most techniques for tag recommendation only two dimensions "resource-user " are considered. But there are three dimensions "resource-user-tag " in recommendation system based on social tags. A new method of social tag recommendation based on content-Feature Vote Tagging ( FVT) is proposed in this paper. Finally,several kinds of evaluation methods are used to assess the return results of methods. The experiment results show that the method proposed in this paper can satisfy the expectation of the user for the recommendation results.展开更多
采用内容分析的方法,对2008、2009年《Social & Cultural Geography》所刊载论文的资料搜集方法、分析方法、佐证材料类型进行了统计。研究发现:西方文化地理研究更倾向于定性研究的取向,强调研究者本身挖掘社会素材的能力和诠释材...采用内容分析的方法,对2008、2009年《Social & Cultural Geography》所刊载论文的资料搜集方法、分析方法、佐证材料类型进行了统计。研究发现:西方文化地理研究更倾向于定性研究的取向,强调研究者本身挖掘社会素材的能力和诠释材料的智慧和客观性。在资料搜集与展示方面,西方学者更加倾向于进行实地研究,多采用参与式观察、访谈等多种方式获取大量的资料,善用文字资料、照片等多种证据来证明研究的信度和效度。本研究希望通过西方经典文化地理文献的梳理,引起国内研究人员对定性研究取向的重视,以及对文本资料、照片等证据作为学术研究成果表达方式的重视。展开更多
目的对基于社交媒体的乳腺癌相关内容分析研究进行范围综述。方法依据范围综述方法学框架,检索Web of Science、PubMed、Cochrane Library、CINAHL、Embase、中国知网、万方和中国生物医学数据库中的相关研究,检索时限为2013年1月1日-2...目的对基于社交媒体的乳腺癌相关内容分析研究进行范围综述。方法依据范围综述方法学框架,检索Web of Science、PubMed、Cochrane Library、CINAHL、Embase、中国知网、万方和中国生物医学数据库中的相关研究,检索时限为2013年1月1日-2023年1月1日,对纳入文献进行汇总和分析。结果最终纳入70篇文献,研究大多数来自美国,发表于2019-2022年。研究以乳腺癌患者或利益相关者作为研究对象,聚焦于社会支持、发帖内容准确性、治疗等主题,更多关注具有广泛受众的社交媒体平台Twitter、Facebook,和乳腺癌特异性社交媒体Breastcancer.org等,多数通过关键词、标签和算法检索帖子进行数据收集,根据帖子数量及研究目的选择人工处理、机器算法等形式,并从主题和情感2个主要维度开展文本、图像等的内容分析。结论目前基于社交媒体的乳腺癌相关内容分析研究关注社会支持和发帖内容的准确性等研究方向,数据分析方法涉及小样本手工分析和大样本机器学习,相关结果丰富了乳腺癌患者及其利益相关人群的需求和体验研究,可为基于患者报告的体验研究提供多样化的研究成果。后续研究可积极探索主流媒体中乳腺癌患者的真实需求及体验,具化各类群体的需求特征,从而基于社交媒体为乳腺癌群体建立精准化的信息服务方案。展开更多
基金supported in part by the National Science Foundation of China,under Grants 71671114,61672350,and U1405251
文摘Recently, there has been a radial shift from traditional online social networks to content-generated social networks(CGSNs). Contemporary CGSNs, such as Dianping and Trip Advisor, are often the targets of click farming in which fake reviews are posted in order to boost or diminish the ratings of listed products and services simply through clicking. Click farming often emanates from a collection of multiple fake or compromised accounts, which we call click farmers. In this paper, we conduct a three-phase methodology to detect click farming. We begin by clustering communities based on newly-defined collusion networks. We then apply the Louvain community detection method to detecting communities. We finally perform a binary classification on detected-communities. Our results of over a year-long study show that(1) the prevalence of click farming is different across CGSNs;(2) most click farmers are lowly-rated;(3) click-farming communities have relatively tight relations between users;(4) more highly-ranked stores have a greater portion of fake reviews.
基金Sponsored by the Heilongjiang Province Science Foundation for Youths(Grant No.QC2011C012)the Harbin Foundation for the Talents of Technology Innovation(Grant No.2012RFQXG095)the Fundamental Research Funds for the Central Universities(Grant No.HEUCF100605)
文摘With the rapid development of the Internet,more and more people begin to pay attention to social tagging which is a flexible and efficient method for classification. How to retrieve tags from the huge tag library becomes a hot topic to research. Firstly,the existing systems of social tags and its recommendation principles used in Web 2. 0 are introduced in this paper. Secondly,the existing techniques about tag recommendation are summarized,and their merits and demerits are analysed. In most techniques for tag recommendation only two dimensions "resource-user " are considered. But there are three dimensions "resource-user-tag " in recommendation system based on social tags. A new method of social tag recommendation based on content-Feature Vote Tagging ( FVT) is proposed in this paper. Finally,several kinds of evaluation methods are used to assess the return results of methods. The experiment results show that the method proposed in this paper can satisfy the expectation of the user for the recommendation results.
文摘采用内容分析的方法,对2008、2009年《Social & Cultural Geography》所刊载论文的资料搜集方法、分析方法、佐证材料类型进行了统计。研究发现:西方文化地理研究更倾向于定性研究的取向,强调研究者本身挖掘社会素材的能力和诠释材料的智慧和客观性。在资料搜集与展示方面,西方学者更加倾向于进行实地研究,多采用参与式观察、访谈等多种方式获取大量的资料,善用文字资料、照片等多种证据来证明研究的信度和效度。本研究希望通过西方经典文化地理文献的梳理,引起国内研究人员对定性研究取向的重视,以及对文本资料、照片等证据作为学术研究成果表达方式的重视。
文摘目的对基于社交媒体的乳腺癌相关内容分析研究进行范围综述。方法依据范围综述方法学框架,检索Web of Science、PubMed、Cochrane Library、CINAHL、Embase、中国知网、万方和中国生物医学数据库中的相关研究,检索时限为2013年1月1日-2023年1月1日,对纳入文献进行汇总和分析。结果最终纳入70篇文献,研究大多数来自美国,发表于2019-2022年。研究以乳腺癌患者或利益相关者作为研究对象,聚焦于社会支持、发帖内容准确性、治疗等主题,更多关注具有广泛受众的社交媒体平台Twitter、Facebook,和乳腺癌特异性社交媒体Breastcancer.org等,多数通过关键词、标签和算法检索帖子进行数据收集,根据帖子数量及研究目的选择人工处理、机器算法等形式,并从主题和情感2个主要维度开展文本、图像等的内容分析。结论目前基于社交媒体的乳腺癌相关内容分析研究关注社会支持和发帖内容的准确性等研究方向,数据分析方法涉及小样本手工分析和大样本机器学习,相关结果丰富了乳腺癌患者及其利益相关人群的需求和体验研究,可为基于患者报告的体验研究提供多样化的研究成果。后续研究可积极探索主流媒体中乳腺癌患者的真实需求及体验,具化各类群体的需求特征,从而基于社交媒体为乳腺癌群体建立精准化的信息服务方案。
