A new direction in social network analysis: Online social network analysis problems and applications

The use of online social networks has made significant progress in recent years as the use of the Internet has become widespread worldwide as the technological infrastructure and the use of technological products evolve. It has become more suitable to reach online social networking sites such as Facebook, Twitter, Instagram and LinkedIn via the internet and web 3.0 technologies. Thus, people have shared their views on many different topics and their emotions with other users more widely on these platforms. This means that a huge amount of data is created on platforms where millions of people connect with each other through social networks. Nevertheless, the development of computational paradigms at high speed and complexity with technological possibilities allows analysis of valuable data by means of social network analysis methods. Our goal for this paper is to present a review of novel and popular online social network analysis problems with related applications and a reference work for researchers interested in analyzing online social network data and social network problems. Unlike other individual studies we have gathered 21 online social network problems and defined them with related studies. Thus, this study is original by presenting an important source of research by explaining the problems of online social network and the studies performed in this area.

[1]  Akshi Kumar,et al.  An Algorithmic Framework for Collaborative Interest Group Construction , 2010 .

[2]  Ying Chen,et al.  Detecting Offensive Language in Social Media to Protect Adolescent Online Safety , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.

[3]  Tony Veale,et al.  Fracking Sarcasm using Neural Network , 2016, WASSA@NAACL-HLT.

[4]  Daling Wang,et al.  Detecting Positive Opinion Leader Group from Forum , 2012, WAIM.

[5]  Yue Xu,et al.  Toward Predicting Susceptibility to Phishing Victimization on Facebook , 2016, 2016 IEEE International Conference on Services Computing (SCC).

[6]  Mohamed Bouguessa,et al.  Identifying Authorities in Online Communities , 2015, ACM Trans. Intell. Syst. Technol..

[7]  Changsheng Xu,et al.  Multi-Modal Event Topic Model for Social Event Analysis , 2016, IEEE Transactions on Multimedia.

[8]  Vijayan Sugumaran,et al.  Building knowledge base of urban emergency events based on crowdsourcing of social media , 2016, Concurr. Comput. Pract. Exp..

[9]  Yi Peng,et al.  Understanding influence power of opinion leaders in e-commerce networks: An opinion dynamics theory perspective , 2018, Inf. Sci..

[10]  Davide Buscaldi,et al.  From humor recognition to irony detection: The figurative language of social media , 2012, Data Knowl. Eng..

[11]  Mohammad Reza Khayyambashi,et al.  An approach for detecting profile cloning in online social networks , 2013, 7th International Conference on e-Commerce in Developing Countries:with focus on e-Security.

[12]  Per A. Hallgren,et al.  InnerCircle: A parallelizable decentralized privacy-preserving location proximity protocol , 2015, 2015 13th Annual Conference on Privacy, Security and Trust (PST).

[13]  Sushil Jajodia,et al.  Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg? , 2012, IEEE Transactions on Dependable and Secure Computing.

[14]  Derek Ruths,et al.  Classifying Political Orientation on Twitter: It's Not Easy! , 2013, ICWSM.

[15]  Chenliang Li,et al.  Twevent: segment-based event detection from tweets , 2012, CIKM.

[16]  Muhammad Abulaish,et al.  A generic statistical approach for spam detection in Online Social Networks , 2013, Comput. Commun..

[17]  Ernesto Damiani,et al.  Location Privacy Protection Through Obfuscation-Based Techniques , 2007, DBSec.

[18]  Hossein Saidi,et al.  Social Networks' XSS Worms , 2009, 2009 International Conference on Computational Science and Engineering.

[19]  Takao Terano,et al.  Detecting rumor patterns in streaming social media , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[20]  Luo Si,et al.  Privacy-Preserving and Efficient Friend Recommendation in Online Social Networks , 2015, Trans. Data Priv..

[21]  Wei Hu,et al.  Twitter spammer detection using data stream clustering , 2014, Inf. Sci..

[22]  Yiannis Kompatsiaris,et al.  Detection and visualization of misleading content on Twitter , 2017, International Journal of Multimedia Information Retrieval.

[23]  Daniele Quercia,et al.  Partisan sharing: facebook evidence and societal consequences , 2014, COSN '14.

[24]  Lizhen Wang,et al.  An approach for overlapping and hierarchical community detection in social networks based on coalition formation game theory , 2015, Expert Syst. Appl..

[25]  Shivakant Mishra,et al.  Analyzing Labeled Cyberbullying Incidents on the Instagram Social Network , 2015, SocInfo.

[26]  Sheikh Iqbal Ahamed,et al.  Preserve Your Privacy with PCO: A Privacy Sensitive Architecture for Context Obfuscation for Pervasive E-Community Based Applications , 2010, 2010 IEEE Second International Conference on Social Computing.

[27]  Feng Xiong,et al.  The use of social media to detect corporate fraud: A case study approach , 2018, Business Horizons.

[28]  Lewis Mitchell,et al.  Tweeting weight loss: A comparison of #thinspiration and #fitspiration communities on Twitter. , 2018, Body image.

[29]  Saif Mohammad,et al.  Detecting Stance in Tweets And Analyzing its Interaction with Sentiment , 2016, *SEMEVAL.

[30]  Véronique Van Vlasselaer,et al.  Fraud Analytics : Using Descriptive, Predictive, and Social Network Techniques:A Guide to Data Science for Fraud Detection , 2015 .

[31]  Tobias Johansson,et al.  Gossip spread in social network models , 2017 .

[32]  Nan Chen,et al.  Constrained NMF-based semi-supervised learning for social media spammer detection , 2017, Knowl. Based Syst..

[33]  Alok N. Choudhary,et al.  Towards Online Spam Filtering in Social Networks , 2012, NDSS.

[34]  Franciska de Jong,et al.  Cyberbullying detection: a step toward a safer internet yard , 2012, WWW.

[35]  Erik Rolland,et al.  Social network meets Sherlock Holmes: investigating the missing links of fraud , 2012 .

[36]  W. Fan,et al.  Online social networks—Paradise of computer viruses☆ , 2011 .

[37]  Mor Naaman,et al.  Towards automatic extraction of event and place semantics from flickr tags , 2007, SIGIR.

[38]  Toru Ishida,et al.  Detecting innovative topics based on user-interest ontology , 2009, J. Web Semant..

[39]  Nam P. Nguyen,et al.  Sources of misinformation in Online Social Networks: Who to suspect? , 2012, MILCOM 2012 - 2012 IEEE Military Communications Conference.

[40]  Wael Khreich,et al.  A Survey of Techniques for Event Detection in Twitter , 2015, Comput. Intell..

[41]  Raymond H. Putra,et al.  Support or Oppose? Classifying Positions in Online Debates from Reply Activities and Opinion Expressions , 2010, COLING.

[42]  Yao Zheng,et al.  SHARP: Private Proximity Test and Secure Handshake with Cheat-Proof Location Tags , 2012, ESORICS.

[43]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[44]  Tianbo Wang,et al.  The Temporal Characteristic of Human Mobility: Modeling and Analysis of Social Worm Propagation , 2015, IEEE Communications Letters.

[45]  Jemal H. Abawajy,et al.  Privacy-preserving multi-hop profile-matching protocol for proximity mobile social networks , 2017, Future Gener. Comput. Syst..

[46]  Hamid Reza Karimi,et al.  The Finding and Dynamic Detection of Opinion Leaders in Social Network , 2014 .

[47]  Sasa Petrovic,et al.  Real-time event detection in massive streams , 2013 .

[48]  V. Uma,et al.  Temporal Sentiment Analysis and Causal Rules Extraction from Tweets for Event Prediction , 2015 .

[49]  Reza Zafarani,et al.  Sarcasm Detection on Twitter: A Behavioral Modeling Approach , 2015, WSDM.

[50]  Julio Gonzalo,et al.  Learning similarity functions for topic detection in online reputation monitoring , 2014, SIGIR.

[51]  Christopher C. Yang,et al.  Using Health-Consumer-Contributed Data to Detect Adverse Drug Reactions by Association Mining with Temporal Analysis , 2015, ACM Trans. Intell. Syst. Technol..

[52]  Mauro Conti,et al.  FakeBook: Detecting Fake Profiles in On-Line Social Networks , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[53]  Kelly Reynolds,et al.  Detecting cyberbullying: query terms and techniques , 2013, WebSci.

[54]  Weili Wu,et al.  Least Cost Rumor Blocking in Social Networks , 2013, 2013 IEEE 33rd International Conference on Distributed Computing Systems.

[55]  Rui Zhao,et al.  Automatic detection of cyberbullying on social networks based on bullying features , 2016, ICDCN.

[56]  Weiqing Sun,et al.  Efficient spam detection across Online Social Networks , 2016, 2016 IEEE International Conference on Big Data Analysis (ICBDA).

[57]  Jong Hyuk Park,et al.  Social network security: Issues, challenges, threats, and solutions , 2017, Inf. Sci..

[58]  Dariusz Król,et al.  On Modelling Social Propagation Phenomenon , 2014, ACIIDS.

[59]  Jie Cao,et al.  A pattern-based topic detection and analysis system on Chinese tweets , 2017, J. Comput. Sci..

[60]  Jun Zhang,et al.  Modeling Propagation Dynamics of Social Network Worms , 2013, IEEE Transactions on Parallel and Distributed Systems.

[61]  Xiuzhen Zhang,et al.  Anomaly detection in online social networks , 2014, Soc. Networks.

[62]  Mohsen Kahani,et al.  Mining user interests over active topics on social networks , 2018, Inf. Process. Manag..

[63]  Huan Liu,et al.  Data Mining in Social Media , 2011, Social Network Data Analytics.

[64]  Edgar R. Weippl,et al.  Social engineering attacks on the knowledge worker , 2013, SIN.

[65]  Leyla Bilge,et al.  All your contacts are belong to us: automated identity theft attacks on social networks , 2009, WWW '09.

[66]  Kenji Araki,et al.  Sustainable cyberbullying detection with category-maximized relevance of harmful phrases and double-filtered automatic optimization , 2016, Int. J. Child Comput. Interact..

[67]  Qi He,et al.  TwitterRank: finding topic-sensitive influential twitterers , 2010, WSDM '10.

[68]  Aaron Smith,et al.  Teens, Kindness and Cruelty on Social Network Sites , 2011 .

[69]  Hui Xiong,et al.  Towards expert finding by leveraging relevant categories in authority ranking , 2011, CIKM '11.

[70]  Keith Stevens,et al.  Event Detection in Blogs using Temporal Random Indexing , 2009 .

[71]  Filippo Menczer,et al.  Hoaxy: A Platform for Tracking Online Misinformation , 2016, WWW.

[72]  Marie-Jeanne Lesot,et al.  Rumour detection and monitoring in open source intelligence: understanding publishing behaviours as a prerequisite , 2010 .

[73]  Preeti S. Voditel,et al.  Spear phishing: Diagnosing attack paradigm , 2017, 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET).

[74]  Jacob Ratkiewicz,et al.  Predicting the Political Alignment of Twitter Users , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[75]  Rachel Young,et al.  Romantic motivations for social media use, social comparison, and online aggression among adolescents , 2017, Comput. Hum. Behav..

[76]  Cameron Marlow,et al.  A 61-million-person experiment in social influence and political mobilization , 2012, Nature.

[77]  Qiang Fu,et al.  Combating the evolving spammers in online social networks , 2018, Comput. Secur..

[78]  J. I. Sheeba,et al.  Online Social Network Bullying Detection Using Intelligence Techniques , 2015 .

[79]  Hamideh Afsarmanesh,et al.  Phishing through social bots on Twitter , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[80]  Diana Maynard,et al.  Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis. , 2014, LREC.

[81]  Naren Ramakrishnan,et al.  Epidemiological modeling of news and rumors on Twitter , 2013, SNAKDD '13.

[82]  Shambhu J. Upadhyaya,et al.  The Early (tweet-ing) Bird Spreads the Worm: An Assessment of Twitter for Malware Propagation , 2012, ANT/MobiWIS.

[83]  José-Ángel González,et al.  ELiRF-UPV at IberEval 2017: Stance and Gender Detection in Tweets , 2017, IberEval@SEPLN.

[84]  Rob Malouf,et al.  Taking sides: user classification for informal online political discourse , 2008, Internet Res..

[85]  Olivier Serrat.  Social Network Analysis , 2009 .

[86]  April Kontostathis,et al.  Text Mining and Cybercrime , 2010 .

[87]  Nam P. Nguyen,et al.  Dynamic Social Community Detection and Its Applications , 2014, PloS one.

[88]  Lei Chen,et al.  Event detection over twitter social media streams , 2013, The VLDB Journal.

[89]  G Nandi,et al.  A Survey on Using Data Mining Techniques for Online Social Network Analysis , 2013 .

[90]  Meera Venkatraman.  Opinion leaders, adopters, and communicative adopters: A role analysis , 1989 .

[91]  Steve Mansfield-Devine,et al.  Social Networking: Anti-social networking: exploiting the trusting environment of Web 2.0 , 2008 .

[92]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[93]  Stefano Faralli,et al.  Automatic acquisition of a taxonomy of microblogs users' interests , 2017, J. Web Semant..

[94]  Qinghua Zheng,et al.  Semi-supervised clue fusion for spammer detection in Sina Weibo , 2018, Inf. Fusion.

[95]  Mahmoud Al-Ayyoub,et al.  Measuring the controversy level of Arabic trending topics on Twitter , 2016, 2016 7th International Conference on Information and Communication Systems (ICICS).

[96]  Man Lung Yiu,et al.  Private and Flexible Proximity Detection in Mobile Social Networks , 2010, 2010 Eleventh International Conference on Mobile Data Management.

[97]  Yang Zhang,et al.  Cyberbullying Detection based on text-stream classification , 2013, AusDM 2013.

[98]  Josef Steinberger,et al.  UWB at SemEval-2016 Task 6: Stance Detection , 2016, *SEMEVAL.

[99]  Salvatore Orlando,et al.  Polarized User and Topic Tracking in Twitter , 2016, SIGIR.

[100]  R. Giora.  On irony and negation , 1995 .

[101]  P. Gloor,et al.  Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear” , 2011 .

[102]  Saif Mohammad,et al.  SemEval-2016 Task 6: Detecting Stance in Tweets , 2016, *SEMEVAL.

[103]  Enhong Chen,et al.  Learning recency based comparative choice towards point-of-interest recommendation , 2015, Expert Syst. Appl..

[104]  Isabelle Szmigin,et al.  The iPod Phenomenon: Identifying a Market Leader?s Secrets Through Qualitative Marketing Research , 2006 .

[105]  Swapna Somasundaran,et al.  Recognizing Stances in Ideological On-Line Debates , 2010, HLT-NAACL 2010.

[106]  Muthucumaru Maheswaran,et al.  Trusted Gossip:A Rumor Resistant Dissemination Mechanism for Peer-to-Peer Information Sharing , 2007, 21st International Conference on Advanced Information Networking and Applications (AINA '07).

[107]  Uyen Trang Nguyen,et al.  A study of clickjacking worm propagation in online social networks , 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

[108]  Kim-Kwang Raymond Choo,et al.  The cyber threat landscape: Challenges and future research directions , 2011, Comput. Secur..

[109]  Kristen LeFevre,et al.  Privacy wizards for social networking sites , 2010, WWW '10.

[110]  Youssef Iraqi,et al.  Phishing Detection: A Literature Survey , 2013, IEEE Communications Surveys & Tutorials.

[111]  Eileen Wood,et al.  All about me: Disclosure in online social networking profiles: The case of FACEBOOK , 2010, Comput. Hum. Behav..

[112]  Vahab S. Mirrokni,et al.  Large-Scale Community Detection on YouTube for Topic Discovery and Exploration , 2011, ICWSM.

[113]  Hossein Saidi,et al.  Malware propagation in Online Social Networks , 2009, 2009 4th International Conference on Malicious and Unwanted Software (MALWARE).

[114]  Pablo Castells,et al.  Extracting multilayered Communities of Interest from semantic user profiles: Application to group modeling and hybrid recommendations , 2011, Comput. Hum. Behav..

[115]  Arun Kumar Sangaiah,et al.  CenLocShare: A centralized privacy-preserving location-sharing system for mobile online social networks , 2017, Future Gener. Comput. Syst..

[116]  Yun Chi,et al.  Identifying opinion leaders in the blogosphere , 2007, CIKM '07.

[117]  Hendri Murfi,et al.  Combination of singular value decomposition and K-means clustering methods for topic detection on Twitter , 2015, 2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS).

[118]  Shivakant Mishra,et al.  Towards understanding cyberbullying behavior in a semi-anonymous social network , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[119]  Sungchang Lee,et al.  Community clustering based on trust modeling weighted by user interests in online social networks , 2017 .

[120]  Li Shang,et al.  ETree: Effective and Efficient Event Modeling for Real-Time Online Social Media Networks , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[121]  Cheng Huang,et al.  Achieve Efficient and Privacy-Preserving Proximity Detection Scheme for Social Applications , 2017, SecureComm.

[122]  Arun Vishwanath,et al.  Habitual Facebook Use and its Impact on Getting Deceived on Social Media , 2015, J. Comput. Mediat. Commun..

[123]  Kevin Driscoll,et al.  The diffusion of misinformation on social media: Temporal pattern, message, and source , 2018, Comput. Hum. Behav..

[124]  Antonios Siganos,et al.  Facebook's daily sentiment and international stock markets , 2014 .

[125]  Marilyn A. Walker,et al.  That is your evidence?: Classifying stance in online political debate , 2012, Decis. Support Syst..

[126]  Benoît Otjacques,et al.  Community extraction and visualization in social networks applied to Twitter , 2018, Inf. Sci..

[127]  P. Gloor,et al.  Predicting Asset Value through Twitter Buzz , 2012 .

[128]  Simon Clematide,et al.  Stance Detection in Facebook Posts of a German Right-wing Party , 2017, LSDSem@EACL.

[129]  Calton Pu,et al.  Click traffic analysis of short URL spam on Twitter , 2013, 9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing.

[130]  Aristides Gionis,et al.  Automatic controversy detection in social media: A content-independent motif-based approach , 2017, Online Soc. Networks Media.

[131]  Donghyun Kim,et al.  Rumor restriction in Online Social Networks , 2013, 2013 IEEE 32nd International Performance Computing and Communications Conference (IPCCC).

[132]  Fan Yang,et al.  Automatic detection of rumor on Sina Weibo , 2012, MDS '12.

[133]  Meina Song,et al.  Social recommendation algorithm fusing user interest social network , 2014 .

[134]  Krishna P. Gummadi,et al.  The Doppelgänger Bot Attack: Exploring Identity Impersonation in Online Social Networks , 2015, Internet Measurement Conference.

[135]  Jianxin Li,et al.  Model-based non-Gaussian interest topic distribution for user retweeting in social networks , 2018, Neurocomputing.

[136]  Hadi S. Aghdasi,et al.  Community detection in social networks with node attributes based on multi-objective biogeography based optimization , 2017, Eng. Appl. Artif. Intell..

[137]  Xiangliang Zhang,et al.  Protecting multi-party privacy in location-aware social point-of-interest recommendation , 2018, World Wide Web.

[138]  Jaideep Srivastava,et al.  Data Mining Techniques for Social Networks Analysis , 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

[139]  Wei Gao,et al.  Rumor Detection on Twitter with Tree-structured Recursive Neural Networks , 2018, ACL.

[140]  Arun Kumar Sangaiah,et al.  A privacy-preserving friend recommendation scheme in online social networks , 2018 .

[141]  Ahmet Bedri Özer,et al.  Web Pages Classification with Parliamentary Optimization Algorithm , 2017, Int. J. Softw. Eng. Knowl. Eng..

[142]  Sarbjeet Singh,et al.  A comparative analysis of structural graph metrics to identify anomalies in online social networks , 2017, Comput. Electr. Eng..

[143]  Ravneet Kaur,et al.  A survey of data mining and social network analysis based anomaly detection techniques , 2016 .

[144]  Joshua Fogel,et al.  Internet social network communities: Risk taking, trust, and privacy concerns , 2009, Comput. Hum. Behav..

[145]  P. Tiňo,et al.  Non-parametric causality detection: An application to social media and financial data , 2016, Physica A: Statistical Mechanics and its Applications.

[146]  Jacob Ratkiewicz,et al.  Political Polarization on Twitter , 2011, ICWSM.

[147]  Stanley Wasserman,et al.  Social Network Analysis: Social Network Analysis in the Social and Behavioral Sciences , 1994 .

[148]  Anja Feldmann,et al.  Understanding online social network usage from a network perspective , 2009, IMC '09.

[149]  James R. Foulds,et al.  Joint Models of Disagreement and Stance in Online Debate , 2015, ACL.

[150]  Ron Bekkerman,et al.  Bimodal invitation-navigation fair bets model for authority identification in a social network , 2012, WWW.

[151]  Xiaodong Lin,et al.  EPPD: Efficient and privacy-preserving proximity testing with differential privacy techniques , 2016, 2016 IEEE International Conference on Communications (ICC).

[152]  Thuy Vu,et al.  Interest mining from user tweets , 2013, CIKM.

[153]  Ari Rappoport,et al.  Semi-Supervised Recognition of Sarcasm in Twitter and Amazon , 2010, CoNLL.

[154]  Dazhen Lin,et al.  Content Representation for Microblog Rumor Detection , 2016, UKCI.

[155]  Vikram Pudi,et al.  Controversy Detection Using Reactions on Social Media , 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

[156]  Pierre Morizet-Mahoudeaux,et al.  A user-centered approach for integrating social data into groups of interest , 2015, Data Knowl. Eng..

[157]  Michele L. Ybarra,et al.  How Risky Are Social Networking Sites? A Comparison of Places Online Where Youth Sexual Solicitation and Harassment Occurs , 2008, Pediatrics.

[158]  Yutaka Matsuo,et al.  Earthquake shakes Twitter users: real-time event detection by social sensors , 2010, WWW '10.

[159]  Ove Andersen,et al.  A Location Privacy Aware Friend Locator , 2009, SSTD.

[160]  Duen-Ren Liu,et al.  Expert finding in question-answering websites: a novel hybrid approach , 2010, SAC '10.

[161]  Dade Nurjanah,et al.  Indonesian Twitter Cyberbullying Detection using Text Classification and User Credibility , 2018, 2018 International Conference on Information and Communications Technology (ICOIACT).

[162]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[163]  Xiao Zhang,et al.  pkudblab at SemEval-2016 Task 6 : A Specific Convolutional Neural Network System for Effective Stance Detection , 2016, *SEMEVAL.

[164]  Yiannis Kompatsiaris,et al.  Community detection in Social Media , 2012, Data Mining and Knowledge Discovery.

[165]  Kai Niu,et al.  Exploiting the topology property of social network for rumor detection , 2015, 2015 12th International Joint Conference on Computer Science and Software Engineering (JCSSE).

[166]  Eunsoo Seo,et al.  Identifying rumors and their sources in social networks , 2012, Defense + Commercial Sensing.

[167]  Bin Zhou,et al.  User interest mining via tags and bidirectional interactions on Sina Weibo , 2017, World Wide Web.

[168]  Cheng Wang,et al.  Identity Theft Detection in Mobile Social Networks Using Behavioral Semantics , 2017, 2017 IEEE International Conference on Smart Computing (SMARTCOMP).

[169]  Rui Zhao,et al.  Cyberbullying Detection Based on Semantic-Enhanced Marginalized Denoising Auto-Encoder , 2017, IEEE Transactions on Affective Computing.

[170]  Jun Sun,et al.  Identifying the most influential topic-sensitive opinion leaders in online review communities , 2016, 2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA).

[171]  Longfei Wu,et al.  MobiFish: A lightweight anti-phishing scheme for mobile phones , 2014, 2014 23rd International Conference on Computer Communication and Networks (ICCCN).

[172]  Ling Chen,et al.  Event detection from flickr data through wavelet-based spatial analysis , 2009, CIKM.

[173]  Ping Yu Hsu,et al.  Detecting Fake Review with Rumor Model- Case Study in Hotel Review , 2015, IScIDE.

[174]  Athena Vakali,et al.  Community Detection in Social Media by Leveraging Interactions and Intensities , 2013, WISE.

[175]  Marilyn A. Walker,et al.  Collective Stance Classification of Posts in Online Debate Forums , 2014 .

[176]  Imene Guellil,et al.  Social big data mining: A survey focused on opinion mining and sentiments analysis , 2015, 2015 12th International Symposium on Programming and Systems (ISPS).

[177]  Ioannis Hatzilygeroudis,et al.  Emotional community detection in social networks , 2017, Comput. Electr. Eng..

[178]  Anazida Zainal,et al.  Fraud detection system: A survey , 2016, J. Netw. Comput. Appl..

[179]  Jian Pei,et al.  A brief survey on anonymization techniques for privacy preserving publishing of social network data , 2008, SKDD.

[180]  Justin W. Patchin,et al.  Cyberbullying and self-esteem. , 2010, The Journal of school health.

[181]  Zheyi Chen,et al.  Detecting spammers on social networks , 2015, Neurocomputing.

[182]  Yuguang Fang,et al.  Privacy-Preserving Verifiable Proximity Test for Location-Based Services , 2014, GLOBECOM 2014.

[183]  Huan Liu,et al.  Mining Social Media: A Brief Introduction , 2012 .

[184]  Arun Vishwanath,et al.  Getting phished on social media , 2017, Decis. Support Syst..

[185]  Dejing Dou,et al.  A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets , 2016, COLING.

[186]  Wei Wu,et al.  The flexible and privacy-preserving proximity detection in mobile social network , 2018, Future Gener. Comput. Syst..

[187]  Herbert L. Colston,et al.  A brief history of irony. , 2007 .

[188]  Mona T. Diab,et al.  Rumor Detection and Classification for Twitter Data , 2015, ArXiv.

[189]  Sukomal Pal,et al.  Recent developments in social spam detection and combating techniques: A survey , 2016, Inf. Process. Manag..

[190]  D. Wall,et al.  Cybercrime, media and insecurity: The shaping of public perceptions of cybercrime1 , 2008 .

[191]  Charu C. Aggarwal,et al.  Community Detection with Edge Content in Social Media Networks , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[192]  Cécile Favre,et al.  Information diffusion in online social networks: a survey , 2013, SGMD.

[193]  Rémy Cazabet,et al.  Detection of Overlapping Communities in Dynamical Social Networks , 2010, 2010 IEEE Second International Conference on Social Computing.

[194]  W. Bruce Croft,et al.  On-line new event detection, clustering, and tracking (information retrieval, internet) , 1999 .

[195]  Ellen Riloff,et al.  Sarcasm as Contrast between a Positive Sentiment and Negative Situation , 2013, EMNLP.

[196]  German Neubaum,et al.  Examining Characteristics of Opinion Leaders in Social Media: A Motivational Approach , 2016 .

[197]  Clement T. Yu,et al.  Topic Sentiment Change Analysis , 2011, MLDM.

[198]  N. Marres.  Why Map Issues? On Controversy Analysis as a Digital Method , 2015, Science, technology & human values.

[199]  Robert Power,et al.  A sensitive Twitter earthquake detector , 2013, WWW.

[200]  Ruifang Liu,et al.  Weighted Graph Clustering for Community Detection of Large Social Networks , 2014, ITQM.

[201]  Feng-Yang Kuo,et al.  Exploring individual communication power in the blogosphere , 2008, Internet Res..

[202]  Huan Liu,et al.  Sentiment Informed Cyberbullying Detection in Social Media , 2017, ECML/PKDD.

[203]  Shona Leitch,et al.  Security Issues Challenging Facebook , 2009 .

[204]  Jun Hu,et al.  Detecting and characterizing social spam campaigns , 2010, CCS '10.

[205]  Zinaida Benenson,et al.  Unpacking Spear Phishing Susceptibility , 2017, Financial Cryptography Workshops.

[206]  Dimitris Spathis,et al.  A comparison between semi-supervised and supervised text mining techniques on detecting irony in greek political tweets , 2016, Eng. Appl. Artif. Intell..

[207]  Fabrício Benevenuto,et al.  Phi.sh/$oCiaL: the phishing landscape through short URLs , 2011, CEAS '11.

[208]  Virgílio A. F. Almeida,et al.  Identifying video spammers in online social networks , 2008, AIRWeb '08.

[209]  Victor I. Chang,et al.  User-defined privacy location-sharing system in mobile online social networks , 2017, J. Netw. Comput. Appl..

[210]  B. Biddle.  RECENT DEVELOPMENTS IN ROLE THEORY , 1986 .

[211]  Qun Li,et al.  Near-pri: Private, proximity based location sharing , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[212]  Johan A. Pouwelse,et al.  A Gossip-Based Distributed Social Networking System , 2009, 2009 18th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises.

[213]  Yiming Yang,et al.  A study of retrospective and on-line event detection , 1998, SIGIR '98.

[214]  Dolf Trieschnigg,et al.  Improving Cyberbullying Detection with User Context , 2013, ECIR.

[215]  Dimitrios Gunopulos,et al.  Detecting Events in Online Social Networks: Definitions, Trends and Challenges , 2016, Solving Large Scale Learning Tasks.

[216]  Bin Li,et al.  Mathematical model for spreading dynamics of social network worms , 2012 .

[217]  P. Santhi Thilagam,et al.  Mining social networks for anomalies: Methods and challenges , 2016, J. Netw. Comput. Appl..

[218]  Noël Crespi,et al.  Alike people, alike interests? Inferring interest similarity in online social networks , 2015, Decis. Support Syst..

[219]  Matthew Andrews,et al.  Reconstruction and analysis of Twitter conversation graphs , 2012, HotSocial '12.

[220]  Roger Wattenhofer,et al.  Word of Mouth: Rumor Dissemination in Social Networks , 2008, SIROCCO.

[221]  Tammo H. A. Bijmolt,et al.  Indicators of opinion leadership in customer networks: self-reports and degree centrality , 2016 .

[222]  Yan Jia,et al.  Mining User Interest in Microblogs with a User-Topic Model , 2014 .

[223]  Fangzhao Wu,et al.  Co-detecting social spammers and spam messages in microblogging via exploiting social contexts , 2016, Neurocomputing.

[224]  Mahmoud Al-Ayyoub,et al.  Studying the controversy in online crowds' interactions , 2017, Appl. Soft Comput..

[225]  Wei Wu,et al.  Automatic Generation of Personalized Annotation Tags for Twitter Users , 2010, NAACL.

[226]  Henryk Krawczyk,et al.  Detection of Roles of Actors in Social Networks Using the Properties of Actors' Neighborhood Structure , 2008, 2008 Third International Conference on Dependability of Computer Systems DepCoS-RELCOMEX.

[227]  N. K. Rana,et al.  Detection and prevention of Profile Cloning in Online Social Networks , 2014, International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014).

[228]  Hassan Takabi,et al.  Towards active detection of identity clone attacks on online social networks , 2011, CODASPY '11.

[229]  Kishan G. Mehrotra,et al.  Controversial Topic Discovery on Members of Congress with Twitter , 2014, Complex Adaptive Systems.

[230]  B. Alatas,et al.  Big Social Network Data and Sustainable Economic Development , 2017 .

[231]  Detlef Schoder,et al.  Predictive Analytics On Public Data - The Case Of Stock Markets , 2013, ECIS.

[232]  Shu Lin,et al.  Parallel Micro Blog Crawler Construction for Effective Opinion Leader Approximation , 2013 .

[233]  Pushpak Bhattacharyya,et al.  Automatic Sarcasm Detection , 2016, ACM Comput. Surv..

[234]  Laurent Vercouter,et al.  Extracting Contextonyms from Twitter for Stance Detection , 2017, ICAART.

[235]  Costas Zafiropoulos,et al.  A Social Networking Exploration of Political Blogging in Greece , 2008, WSKS.

[236]  Xiaoming Zhang,et al.  Event detection and popularity prediction in microblogging , 2015, Neurocomputing.

[237]  Ji-Rong Wen,et al.  Finding regions of interest using location based social media , 2016, Neurocomputing.

[238]  Youn-Kyung Kim,et al.  Personality factors and flow affecting opinion leadership in social media , 2017 .

[239]  Jianliang Xu,et al.  Nearby Friend Alert: Location Anonymity in Mobile Geosocial Networks , 2013, IEEE Pervasive Computing.

[240]  Monica K. Nordvik,et al.  Identification of potential opinion leaders in child health promotion in Sweden using network analysis , 2012, BMC Research Notes.

[241]  Bo Jiang,et al.  Modeling Temporal Dynamics of User Interests in Online Social Networks , 2015, ICCS.

[242]  Liang Liu,et al.  Modeling and analyzing malware propagation in social networks with heterogeneous infection rates , 2018, Physica A: Statistical Mechanics and its Applications.

[243]  John Yen,et al.  An LDA-based Community Structure Discovery Approach for Large-Scale Social Networks , 2007, 2007 IEEE Intelligence and Security Informatics.

[244]  Kasturi Dewi Varathan,et al.  Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network , 2016, Comput. Hum. Behav..

[245]  Song Junde,et al.  Textual-geographical-social aware point-of-interest recommendation , 2016 .

[246]  Jun-Ming Xu,et al.  Learning from Bullying Traces in Social Media , 2012, NAACL.

[247]  Jong Hyuk Park,et al.  SpamSpotter: An efficient spammer detection framework based on intelligent decision support system on Facebook , 2017, Appl. Soft Comput..

[248]  Ana-Maria Popescu,et al.  Detecting controversial events from twitter , 2010, CIKM.

[249]  Roberto Henriques,et al.  Social Market: Stock Market and Twitter Correlation , 2017, KES-IDT.

[250]  Nima Jafari Navimipour,et al.  Opinion leaders selection in the social networks based on trust relationships propagation , 2016 .

[251]  A. J. Morales,et al.  Measuring Political Polarization: Twitter shows the two sides of Venezuela , 2015, Chaos.

[252]  Calton Pu,et al.  SPADE: a social-spam analytics and detection framework , 2014, Social Network Analysis and Mining.

[253]  Jie Cao,et al.  TIDM: Topic-Specific Information Detection Model , 2017, ITQM.

[254]  Véronique Hoste,et al.  SemEval-2018 Task 3: Irony Detection in English Tweets , 2018, *SEMEVAL.

[255]  Xin Chen,et al.  Detecting Hot Topics in Sina Weibo Based on Opinion Leaders , 2014, INFOCOM 2014.

[256]  Michalis Vazirgiannis,et al.  An Optimization Approach for Sub-event Detection and Summarization in Twitter , 2018, ECIR.

[257]  Arkaitz Zubiaga,et al.  Detection and Resolution of Rumours in Social Media , 2017, ACM Comput. Surv..

[258]  Paolo Rosso,et al.  Irony, Sarcasm, and Sentiment Analysis , 2017 .

[259]  Hong Guo,et al.  Computer Virus Propagation in Social Networks , 2007, ICIS.

[260]  Aristides Gionis,et al.  Social Network Analysis and Mining for Business Applications , 2011, TIST.

[261]  Marc Van Audenrode,et al.  Can social media data lead to earlier detection of drug‐related adverse events? , 2016, Pharmacoepidemiology and drug safety.

[262]  Xiao Chen,et al.  6 million spam tweets: A large ground truth for timely Twitter spam detection , 2015, 2015 IEEE International Conference on Communications (ICC).

[263]  Supeng Leng,et al.  Malware propagation analysis in message-recallable online social networks , 2017, 2017 IEEE 17th International Conference on Communication Technology (ICCT).

[264]  Rui Li,et al.  TEDAS: A Twitter-based Event Detection and Analysis System , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[265]  Oren Etzioni,et al.  Open domain event extraction from twitter , 2012, KDD.

[266]  Divya,et al.  Techniques to Detect Spammers in Twitter- A Survey , 2014 .

[267]  Guanhua Yan,et al.  Malware propagation in online social networks: nature, dynamics, and defense implications , 2011, ASIACCS '11.

[268]  Tetsuro Takahashi,et al.  Rumor detection on twitter , 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

[269]  Sotiris Ioannidis,et al.  Detecting social network profile cloning , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[270]  Nada Lavrac,et al.  Stream-based active learning for sentiment analysis in the financial domain , 2014, Inf. Sci..

[271]  Claire Cardie,et al.  A Measure of Polarization on Social Media Networks Based on Community Boundaries , 2013, ICWSM.

[272]  Yonghe Zhang,et al.  An improved mix framework for opinion leader identification in online learning communities , 2013, Knowl. Based Syst..

[273]  Carlo Ratti,et al.  A General Optimization Technique for High Quality Community Detection in Complex Networks , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[274]  Boris A. Galitsky.  Detecting Rumor and Disinformation by Web Mining , 2015, AAAI Spring Symposia.

[275]  Albert Y. Zomaya,et al.  Detecting users' anomalous emotion using social media for business intelligence , 2017, J. Comput. Sci..

[276]  Sally M. Kift,et al.  Cyberbullying in Social Networking Sites and Blogs: Legal Issues for Young People and Schools , 2009 .

[277]  Dragomir R. Radev,et al.  Rumor has it: Identifying Misinformation in Microblogs , 2011, EMNLP.

[278]  Themis Palpanas,et al.  Scalable discovery of contradictions on the web , 2010, WWW '10.

[279]  Mehmet Kaya,et al.  Link prediction methods in bipartite networks , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).

[280]  K. Senthamarai Kannan,et al.  Comparative Analysis of Community Discovery Methods in Social Networks , 2011 .

[281]  Jinquan Zeng,et al.  Rumor Identification in Microblogging Systems Based on Users’ Behavior , 2015, IEEE Transactions on Computational Social Systems.

[282]  Nam P. Nguyen,et al.  A novel method for worm containment on dynamic social networks , 2010, 2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE.

[283]  Feng Li,et al.  Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs , 2011, Decis. Support Syst..

[284]  Danah Boyd,et al.  Detecting Spam in a Twitter Network , 2009, First Monday.

[285]  Robin M. Kowalski,et al.  Cyberbullying Via Social Media , 2015 .

[286]  Pradip Kumar Bala,et al.  Sarcasm detection in microblogs using Naïve Bayes and fuzzy clustering , 2017 .

[287]  Nina Wacholder,et al.  Identifying Sarcasm in Twitter: A Closer Look , 2011, ACL.

[288]  Tianqing Zhu,et al.  Wormhole: The Hidden Virus Propagation Power of the Search Engine in Social Networks , 2019, IEEE Transactions on Dependable and Secure Computing.

[289]  James Caverlee,et al.  Detecting Spam URLs in Social Media via Behavioral Analysis , 2015, ECIR.

[290]  Xiaomo Liu,et al.  Real-time Rumor Debunking on Twitter , 2015, CIKM.

[291]  Ponnurangam Kumaraguru,et al.  PhishAri : Automatic Realtime Phishing Detection on Twitter Anupama Aggarwal , 2012 .

[292]  Daniel M. Romero,et al.  Influence and passivity in social media , 2010, ECML/PKDD.

[293]  Qun Jin,et al.  User role identification based on social behavior and networking analysis for information dissemination , 2017, Future Gener. Comput. Syst..

[294]  Soo-Min Kim,et al.  Crystal: Analyzing Predictive Opinions on the Web , 2007, EMNLP.

[295]  Christian S. Jensen,et al.  Location-Related Privacy in Geo-Social Networks , 2011, IEEE Internet Computing.

[296]  Huan Liu,et al.  Discovering Overlapping Groups in Social Media , 2010, 2010 IEEE International Conference on Data Mining.

[297]  Randy Goebel,et al.  Local Community Identification in Social Networks , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.

[298]  Georgia Koutrika,et al.  Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges , 2007, IEEE Internet Computing.

[299]  Wei Xu,et al.  Toward worm detection in online social networks , 2010, ACSAC '10.

[300]  Junjie Chen,et al.  Social Network Rumors Spread Model Based on Cellular Automata , 2014, 2014 10th International Conference on Mobile Ad-hoc and Sensor Networks.

[301]  Mohammad Abdollahi Azgomi,et al.  A Taxonomy of Frauds and Fraud Detection Techniques , 2009, ICISTM.

[302]  Peter A. Gloor,et al.  Predicting Movie Success and Academy Awards through Sentiment and Social Network Analysis , 2008, ECIS.

[303]  Zoey Chen,et al.  When, Why, and How Controversy Causes Conversation , 2012 .

[304]  Qinghua Zheng,et al.  Detecting global and local topics via mining twitter data , 2018, Neurocomputing.

[305]  Yukari Shirota,et al.  Rumor analysis framework in social media , 2011, TENCON 2011 - 2011 IEEE Region 10 Conference.

[306]  Weiguo Fan,et al.  The power of social media analytics , 2014, CACM.

[307]  Krishna P. Gummadi,et al.  Measuring User Influence in Twitter: The Million Follower Fallacy , 2010, ICWSM.

[308]  Horacio Saggion,et al.  Modelling Irony in Twitter , 2014, EACL.

[309]  João Gama,et al.  Online Social Networks Event Detection: A Survey , 2016, Solving Large Scale Learning Tasks.

[310]  Rodica Potolea,et al.  Opinion Leader Detection , 2017 .

[311]  Marilyn A. Walker,et al.  Cats Rule and Dogs Drool!: Classifying Stance in Online Debate , 2011, WASSA@ACL.

[312]  Sameep Mehta,et al.  A study of rumor control strategies on social networks , 2010, CIKM.

[313]  L. Postman,et al.  The psychology of rumor , 1947 .

[314]  Uyen Trang Nguyen,et al.  A Study of XSS Worm Propagation and Detection Mechanisms in Online Social Networks , 2013, IEEE Transactions on Information Forensics and Security.

[315]  Kenli Li,et al.  An effective hot topic detection method for microblog on spark , 2018, Appl. Soft Comput..

[316]  Alex Hai Wang,et al.  Don't follow me: Spam detection in Twitter , 2010, 2010 International Conference on Security and Cryptography (SECRYPT).

[317]  Danushka Bollegala,et al.  Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach , 2018, JMIR public health and surveillance.

[318]  Bushra Siddique,et al.  On Hierarchical Visualization of Event Detection in Twitter , 2018 .

[319]  Yücel Saygin,et al.  Sentimental causal rule discovery from Twitter , 2014, Expert Syst. Appl..

[320]  Hayder Radha,et al.  Identifying Leaders and Followers in Online Social Networks , 2013, IEEE Journal on Selected Areas in Communications.

[321]  Sushil Jajodia,et al.  Privacy-Aware Proximity Based Services , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[322]  Gillian Dobbie,et al.  Phishing Detection on Twitter Streams , 2016, PAKDD Workshops.

[323]  Ronald Rousseau,et al.  Social network analysis: a powerful strategy, also for the information sciences , 2002, J. Inf. Sci..

[324]  Nick Koudas,et al.  Efficient identification of starters and followers in social media , 2009, EDBT '09.

[325]  Phil McKenna.  The rise of cyberbullying , 2007 .

[326]  Chun Chen,et al.  User Modeling for Recommendation in Blogspace , 2007, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops.

[327]  Brian J. Taylor,et al.  Causal discovery in social media using quasi-experimental designs , 2010, SOMA '10.

[328]  Matthew Michelson,et al.  Tweet Disambiguate Entities Retrieve Folksonomy SubTree Step 1 : Discover Categories Generate Topic Profile from SubTrees Step 2 : Discover Profile Topic Profile : “ English Football ” “ World Cup ” , 2010 .

[329]  Bing-Hong Liu,et al.  Virus infection control in online social networks based on probabilistic communities , 2014, Int. J. Commun. Syst..

[330]  Eric Gilbert,et al.  Widespread Worry and the Stock Market , 2010, ICWSM.

[331]  Charles r. Taylor,et al.  Voluntary self‐disclosure of information on the Internet: A multimethod study of the motivations and consequences of disclosing information on blogs , 2008 .

[332]  Sun Hyoung Kim,et al.  Political polarization on twitter: Implications for the use of social media in digital governments , 2016, Gov. Inf. Q..

[333]  Xing Zhou,et al.  Real-Time News Cer tification System on Sina Weibo , 2015, WWW.

[334]  Pengfei Wang,et al.  An algorithm for event detection based on social media data , 2017, Neurocomputing.

[335]  Raymond K. Wong,et al.  Over-Fitting and Error Detection for Online Role Mining , 2012, Int. J. Web Serv. Res..

[336]  Antal van den Bosch,et al.  The perfect solution for detecting sarcasm in tweets #not , 2013, WASSA@NAACL-HLT.

[337]  Halit Oguztüzün,et al.  Semantic Expansion of Tweet Contents for Enhanced Event Detection in Twitter , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[338]  Paolo Rosso,et al.  A multidimensional approach for detecting irony in Twitter , 2013, Lang. Resour. Evaluation.

[339]  Vincent Ng,et al.  Stance Classification of Ideological Debates: Data, Models, Features, and Constraints , 2013, IJCNLP.

[340]  Sree Hari Krishnan Parthasarathi,et al.  Exploiting innocuous activity for correlating users across sites , 2013, WWW.

[341]  James Allan,et al.  Introduction to topic detection and tracking , 2002 .

[342]  L. Akoglu.  Quantifying Political Polarity Based on Bipartite Opinion Networks , 2014, ICWSM.

[343]  David Robinson,et al.  Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network , 2018, ESWC.

[344]  Nima Jafari Navimipour,et al.  A new method for trust and reputation evaluation in the cloud environments using the recommendations of opinion leaders' entities and removing the effect of troll entities , 2016, Comput. Hum. Behav..

[345]  Nam P. Nguyen,et al.  Adaptive algorithms for detecting community structure in dynamic social networks , 2011, 2011 Proceedings IEEE INFOCOM.

[346]  Xiaohui Yu,et al.  ARSA: a sentiment-aware model for predicting sales performance using blogs , 2007, SIGIR.

[347]  Eiji Aramaki,et al.  How do rumors spread during a crisis?: Analysis of rumor expansion and disaffirmation on Twitter after 3.11 in Japan , 2014, Int. J. Web Inf. Syst..

[348]  Hugues Sampasa-Kanyinga,et al.  Associations between Cyberbullying and School Bullying Victimization and Suicidal Ideation, Plans and Attempts among Canadian Schoolchildren , 2014, PloS one.

[349]  Punam Bedi,et al.  Community detection in social networks , 2016, WIREs Data Mining Knowl. Discov..

[350]  Mario Cataldi,et al.  Emerging topic detection on Twitter based on temporal and social terms evaluation , 2010, MDMKDD '10.

[351]  Jeffrey Nichols,et al.  Modeling User Attitude toward Controversial Topics in Online Social Media , 2014, ICWSM.

[352]  Yang Liu,et al.  Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment , 2015, IEEE Transactions on Computational Social Systems.

[353]  Tu Shouzhong,et al.  Mining microblog user interests based on TextRank with TF-IDF factor , 2016 .

[354]  Fabián Riquelme,et al.  Measuring user influence on Twitter: A survey , 2015, Inf. Process. Manag..

[355]  Bernardo A. Huberman,et al.  Predicting the Future with Social Media , 2010, Web Intelligence.

[356]  Krishna P. Gummadi,et al.  Cognos: crowdsourcing search for topic experts in microblogs , 2012, SIGIR '12.

[357]  Suely Oliveira,et al.  Community Detection Algorithm for Big Social Networks Using Hybrid Architecture , 2017, Big Data Res..

[358]  Huan Liu,et al.  Community Detection and Mining in Social Media , 2010, Community Detection and Mining in Social Media.

[359]  Kwang-Cheng Chen,et al.  On Modeling Malware Propagation in Generalized Social Networks , 2011, IEEE Communications Letters.

[360]  Barbara Carminati,et al.  Knowledge‐based approaches for identity management in online social networks , 2018, WIREs Data Mining Knowl. Discov..

[361]  Swapna Somasundaran,et al.  Recognizing Stances in Online Debates , 2009, ACL.

[362]  Ari Rappoport,et al.  ICWSM - A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews , 2010, ICWSM.

[363]  Freimut Bodendorf,et al.  Detecting Opinion Leaders and Trends in Online Communities , 2010, 2010 Fourth International Conference on Digital Society.

[364]  Aristides Gionis,et al.  Quantifying Controversy on Social Media , 2018, ACM Trans. Soc. Comput..

[365]  Guilin Qi,et al.  Detecting bursts in sentiment-aware topics from social media , 2018, Knowl. Based Syst..

[366]  Abhishek Singhal,et al.  Dynamic Classification Mining Techniques for Predicting Phishing URL , 2018 .

[367]  Wei Niu,et al.  BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media , 2015, CIKM.

[368]  Jose Emmanuel Ramirez-Marquez,et al.  Visual analytics for identifying product disruptions and effects via social media , 2019, International Journal of Production Economics.

[369]  J. A. Barnes.  Class and Committees in a Norwegian Island Parish , 1954 .

[370]  Brij B. Gupta,et al.  Auditing Defense against XSS Worms in Online Social Network-Based Web Applications , 2016 .

[371]  Jian Dong,et al.  Automatic Detection of Rumor on Social Network , 2015, NLPCC.

[372]  Ryan A. Rossi,et al.  Role Discovery in Networks , 2014, IEEE Transactions on Knowledge and Data Engineering.

[373]  Jun Zhang,et al.  Addressing the class imbalance problem in Twitter spam detection using ensemble learning , 2017, Comput. Secur..

[374]  Kyomin Jung,et al.  Aspects of Rumor Spreading on a Microblog Network , 2013, SocInfo.

[375]  Hung-Min Sun,et al.  A defence scheme against Identity Theft Attack based on multiple social networks , 2014, Expert Syst. Appl..

[376]  Patrick F. Bruning,et al.  Using online opinion leaders to promote the hedonic and utilitarian value of products and services , 2018 .

[377]  Suhang Wang,et al.  Fake News Detection on Social Media: A Data Mining Perspective , 2017, SKDD.

[378]  Ming Li,et al.  FindU: Privacy-preserving personal profile matching in mobile social networks , 2011, 2011 Proceedings IEEE INFOCOM.

[379]  Farshad Safaei,et al.  A statistical infinite feature cascade-based approach to anomaly detection for dynamic social networks , 2017, Comput. Commun..

[380]  Kristofer Beck,et al.  Analyzing tweets to identify malicious messages , 2011, 2011 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY.

[381]  Paolo Rosso,et al.  Irony Detection in Twitter , 2016, ACM Trans. Internet Techn..

[382]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[383]  Eric Gilbert,et al.  Blogs Are Echo Chambers: Blogs Are Echo Chambers , 2009 .

[384]  Kristina Lerman,et al.  The Role of Social Media in the Discussion of Controversial Topics , 2013, 2013 International Conference on Social Computing.

[385]  I-Hsien Ting,et al.  Discovering interest groups for marketing in virtual communities: An integrated approach , 2013 .

[386]  Hongyan Liu,et al.  Detecting Event Rumors on Sina Weibo Automatically , 2013, APWeb.

[387]  Piotr Bródka,et al.  Profile Cloning Detection in Social Networks , 2014, 2014 European Network Intelligence Conference.

[388]  E. Poovammal,et al.  An Analysis of Overlapping Community Detection Algorithms in Social Networks , 2016 .

[389]  P. Waszak,et al.  The spread of medical fake news in social media – The pilot quantitative study , 2018, Health Policy and Technology.

[390]  Ana-Maria Popescu,et al.  Extracting events and event descriptions from Twitter , 2011, WWW.

[391]  Nitin Agarwal,et al.  Modeling blogger influence in a community , 2011, Social Network Analysis and Mining.

[392]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[393]  N. Asokan,et al.  PeerSense: Who is near you? , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications Workshops.

[394]  D. Boyd,et al.  Dynamic Debates: An Analysis of Group Polarization Over Time on Twitter , 2010 .

[395]  Junseok Hwang,et al.  Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach , 2012 .

[396]  Shucheng Yu,et al.  SBPA: Social behavior based cross Social Network phishing attacks , 2016, 2016 IEEE Conference on Communications and Network Security (CNS).

[397]  Miguel Pironet San-Bento Almeida,et al.  Classification for Fraud Detection with Social Network Analysis , 2009 .