Opinion Spamming in Social Media: A Brief Systematic Review

被引:0
作者
Baharim, Khairul Nizam [1 ,2 ]
Hamid, Suraya [1 ]
机构
[1] Univ Malaya, Kuala Lumpur, Wilayah Perseku, Malaysia
[2] TM Res & Dev, Cyberjaya, Selangor, Malaysia
来源
PROCEEDINGS OF KNOWLEDGE MANAGEMENT INTERNATIONAL CONFERENCE (KMICE) 2016 | 2016年
关键词
Opinion spamming detection; Opinion spam; Review spam; Fake reviews; Social media; Survey;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Opinion spamming in social media is an activity of people giving or sharing fake reviews or irrelevant opinions to online communities. The fake reviews are not merely misguided sentiment analysis and opinion mining system, but also severely affected online communities' decision and businesses reputation. Thus, opinion spamming detection (OSD) technique is needed to enhance an opinion mining system and prevent such cases from happening to the online communities. This study was conducted using the systematic literature review (SLR) procedure to classify known opinion spam features in social media platforms, and to reveal types of social media platforms that are being addressed by OSD's researchers. The result is, we found that, spatial and temporal factors in reviewer feature type is a current issue and is important to be solved because of spammer always changing their spamming strategy. On the other hand, most of the studies leveraged n-gram character and part-of-speech approaches in a review feature type because of its significant improved OSD's accuracy. Furthermore, we found that, most of the studies focused on trading and marketing-based social media platform, in which a lack of OSD's study in other forms of social media platforms i.e. social networking and user generated content sites.
引用
收藏
页码:156 / 161
页数:6
相关论文
共 24 条
[1]  
[Anonymous], 2011, Proceedings of the 2011 IEEE 11th International Conference on Data Mining, DOI DOI 10.1109/ICDM.2011.124
[2]  
Banerjee S, 2014, 2014 SCIENCE AND INFORMATION CONFERENCE (SAI), P938, DOI 10.1109/SAI.2014.6918299
[3]  
Competition and Markets Authority, 2015, CMA ACTS MAINT TRUST
[4]  
Fei Geli., 2013, ICWSM
[5]  
Griffith-Greene M., 2014, CBC NEWS
[6]   Detection of review spam: A survey [J].
Heydari, Atefeh ;
Tavakoli, Mohammad Ali ;
Salim, Naomie ;
Heydari, Zahra .
EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (07) :3634-3642
[7]  
Jindal N, 2008, P INT C WEB SEARCH W, P219, DOI DOI 10.1145/1341531.1341560
[8]  
Jindal N, 2007, IEEE DATA MINING, P547, DOI 10.1109/ICDM.2007.68
[9]  
Jindal Nitin., 2010, Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, P1549
[10]   Users of the world, unite! The challenges and opportunities of Social Media [J].
Kaplan, Andreas M. ;
Haenlein, Michael .
BUSINESS HORIZONS, 2010, 53 (01) :59-68