社交网络中的虚假信息:定义、检测及控制

doi:10.11896/jsjkx.210300053

Abstract

Abstract: In recent years,the spread of false information on social networks has become increasingly fierce,causing serious social impact in political,economic,psychological and other aspects.Effective detection and control of false information in social networks is an important means to improve the quality of social network ecosystem and create a safe and credible network environment for people.This paper investigates the representative research in the field of false information of social networks at home and abroad in recent years,combs and gives its definition,characteristics and communication model for false news and rumors in false information,and then introduces various means and methods of detection and communication control of false information at present.Finally,this paper summarizes and analyzes the existing problems of detection and control methods,and then further discusses and puts forward the future research direction in this field.

Key words: Communication control, Fake news, False information detection, Rumor, Social network

CLC Number:

TP391

WANG Jian, WANG Yu-cui, HUANG Meng-jie. False Information in Social Networks:Definition,Detection and Control[J].Computer Science, 2021, 48(8): 263-277.

References

[1]VOSOUGHI S,ROY D,ARAL S.The spread of true and false news online[J].Science,2018,359(6380):1146-1151.
[2]FALLIS D.What is Disinformation?[J].Library Trends,2015,63(3):401-426.
[3]KUMAR S,SHAH N.False Information on Web and SocialMedia:A Survey[EB/OL].(2018-04-23) [2021-02-25].https://arxiv.org/pdf/1804.08559.
[4]BONDIELLI A,MARCELLONI F.A survey on fake news and rumour detection techniques[J].Information Sciences,2019,497:38-55.
[5]HORNE B D,ADALI S.This just in:fake news packs a lot in title,uses simpler,repetitive content in text body,more similar to satire than real news[EB/OL].(2017-03-28) [2021-02-25].https://arxiv.org/pdf/1703.09398.
[6]KUMAR S,WEST R,LESKOVEC J.Disinformation on theweb:Impact,characteristics,and detection of wikipedia hoaxes[C]//Proceedings of the 25th International Conference on World Wide Web.2016.
[7]MATSUBARA Y,SAKURAI Y,PRAKASH B A,et al.Rise and fall patterns of information diffusion:Model and implications[C]//Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD '12).New York,NY:ACM Press,2012:6-14.
[8]LIU Y Z,WANG J,PAN X Z,et al.Research on scale-free network rumor propagation under the influence of nodes[J].Small and Microcomputer System,2018,39(11):2375-2379.
[9]FOSTER E K,ROSNOW R L.Gossip and Network Relationships[M]//Relating difficulty:The processes of constructing and managing difficult interaction.Mahwah,NJ,US:Lawrence Erlbaum Associates Publishers,2006:161-180.
[10]ZENG L,STARBIRD K,SPIRO E S.Rumors at the Speed of Light? Modeling the Rate of Rumor Transmission During Crisis[C]//Proceedings of the 49th Annual Hawaii International Conference on System Sciences (hicss 2016).Los Alamitos,CA:IEEE Computer Society,2016:1969-1978.
[11]FRIGGERI A,ADAMIC L,ECKLES D,et al.Rumor Cascades [C]//Proceedings of the International AAAI Conference on Web and Social Media.Palo Alto,CA:AAAI Press,2014:101-110.
[12]GUPTA A,LAMBA H,KUMARAGURU P,et al.FakingSandy:characterizing and identifying fake images on Twitter during Hurricane Sandy[C]//Proceedings of the 22nd International Conference on World Wide Web-WWW'13 Companion.New York,NY:ACM Press,2013:729-736.
[13]SHAO C,CIAMPAGLIA G L,FLAMMINI A,et al.Hoaxy:APlatform for Tracking Online Misinformation[C]//Proceedings of the 25th International Conference Companion on World Wide Web-WWW'16 Companion.New York,NY:ACM Press,2016:745-750.
[14]ZUBIAGA A,LIAKATA M,PROCTER R,et al.AnalysingHow People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads[J].PLOS ONE,2016,11(3):e0150989.
[15]SUDBURY A.The proportion of the population never hearing a rumour[J].Journal of applied probability,1985,22(2):443-446.
[16]HURLEY M,JACOBS G,GILBERT M.The basic SI model[J].New Directions for Teaching and Leaming,2006,106(6):11-22.
[17]PASTOR-SATORRAS R,VESPIGNANI A.Epidemic dynamics and endemic states in complex networks[J].Physical Review E,2001,63(6):066117.
[18]MORENO Y,PASTOR-SATORRAS R,VESPIGNANI A.Epidemic outbreaks in complex heterogeneous networks[J].The European Physical Journal B,2002,26(4):521-529.
[19]JIN Y,WANG W,XIAO S.An SIRS model with a nonlinear incidence rate[J].Chaos Solitons Fractals,2007,34,1482-1497.
[20]SANG C,LI T,TIAN S,et al.SFTRD:A novel informationpropagation model in heterogeneous networks:Modeling and restraining strategy[J].Physica A:Statistical Mechanics and its Applications,2019,524:475-490.
[21]ZHANG N,HUANG H,SU B,et al.Dynamic 8-state ICSAR rumor propagation model considering official rumor refutation[J].Physica A:Statistical Mechanics and its Applications,2014,415:333-346.
[22]RUAN Z,YU B,SHU X,et al.The impact of malicious nodes on the spreading of false information[J].Chaos:An Interdisciplinary Journal of Nonlinear Science,2020,30(8):083101.
[23]LI J,SONG B,LUO C,et al.Considering Self-media Influence Network Rumor Propagation Model and Control Strategy[C]//2020 IEEE 4th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC).New York,NY:IEEE,2020:1407-1411.
[24]GOLDENBERG J,LIBAI B,MULLER E.Talk of the Network:A Complex Systems Look at the Underlying Process of Word-of-Mouth[J].Marketing Letters,2001,12(3):211-223.
[25]GRANOVETTER M.Threshold Models of Collective Behavior[J].American Journal of Sociology,1978,83(6):1420-1443.
[26]CAMERER C F.Behavioral game theory:Experiment in strategic interaction[J].Socio-Econom,2003,32:135-146.
[27]ZHAO Z,CHEN X.Propagation Model of Derivative RumorConsidering Propagation Error and Malicious Tampering[C]//2019 IEEE 4th International Conference on Big Data Analytics (ICBDA).New York,NY:IEEE,2019:241-245.
[28]HANG Q F,ZHU J M,SONG B,et al.Game model of information transmission in social networks[J].Journal of Chinese Computer Systems,2014,35:473-477.
[29]WANG Y,YU J,QU W,et al.Evolutionary game model andanalysis methods for network group behavior[J].Chin.J.Comput.2015,38:282-300.
[30]ZHOU X,ZAFARANI R.A Survey of Fake News:Fundamental Theories,Detection Methods,and Opportunities[J].ACM Computing Surveys,2020,53(5):1-40.
[31]MITRA T,GILBERT E.CREDBANK:A Large-Scale SocialMedia Corpus With Associated Credibility Annotations[C]//Proceedings of the International AAAI Conference on Web and Social Media.Palo Alto,Calif:AAAI Press,2015.
[32]QAZVINIAN V,ROSENGREN E,RADEV D,et al.Rumor hasit:Identifying misinformation in microblogs[C]//Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing.Stroudsburg,PA:ACL,2011:1589-1599.
[33]KWON S,CHA M,JUNG K,et al.Prominent Features of Rumor Propagation in Online Social Media[C]//2013 IEEE 13th International Conference on Data Mining.Piscataway,NJ:IEEE,2013:1103-1108.
[34]RASHKIN H,CHOI E,JANG J Y,et al.Truth of VaryingShades:Analyzing Language in Fake News and Political Fact-Checking[C]//Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.Stroudsburg,PA:ACL,2017:2931-2937.
[35]MA J,GAO W,WEI Z,et al.Detect Rumors Using Time Series of Social Context Information on Microblogging Websites[C]//Proceedings of the 24th ACM International on Conference on Information and Knowledge Management.New York,NY:ACM,2015:1751-1754.
[36]WU K,YANG S,ZHU K Q.False rumors detection on sinaweibo by propagation structures[C]//2015 IEEE 31st International Conference on Data Engineering.Piscataway,NJ:IEEE,2015:651-662.
[37]LIU Y,XU S.Detecting rumors through modeling information propagation networks in a social media environment[J].IEEE Transactions on Computational Social Systems,2016,3(2):46-62.
[38]MANISH G,ZHAO P X,HAN J W.Evaluating event credibility ontwitter[C]//Proceedings of the 2012 SIAM International Conference on Data Mining.Philadelphia,PA:SIAM,2012:153-164.
[39]MA J,GAO W,WONG K F.Detect rumors in microblog posts using propagation structure via kernel learning[C]//55th An-nual Meeting of the Association-for-Computational-Linguistics (ACL).2017:708-717.
[40]VOLKOVA S,JANG J Y.Misleading or falsification:Inferring deceptive strategies and types in online news and social media[C]//Companion Proceedings of the The Web Conference 2018.New York,NY:ACM,2018:575-583.
[41]JOOYEON K,DONGKWWA K,ALICE O.Homogeneity-based transmissive process to model true and false news in social networks[C]//Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining.New York,NY:ACM,2019:348-356.
[42]POTTHAST M,KIESEL J,REINARTZ K,et al.A Stylometric Inquiry into Hyperpartisan and Fake News[EB/OL].(2017-02-18) [2021-02-25].https://arxiv.org/pdf/1702.05638.
[43]VEDOVA M L D,TACCHINI E,MORET S,et al.Automatic online fake news detection combining content and social signals[C]//2018 22nd Conference of Open Innovations Association (FRUCT).Piscataway,NJ:IEEE,2018:272-279.
[44]SHU K,WANG S,LIU H.Beyond news contents:The role of social context for fake news detection[C]//Proceedings of the twelfth ACM international conference on web search and data mining.New York,NY:ACM,2019:312-320.
[45]POUYANFAR S,SADIQ S,YAN Y,et al.A Survey on Deep Learning:Algorithms,Techniques,and Applications[J].ACM Comput.Surv.,2018,51(5).
[46]LECUN Y,BENGIO Y,HINTON G.Deep learning[J].NATURE,2015,521(7553):436-444.
[47]LIU Y,WU Y F.Early Detection of Fake News on Social Media Through Propagation Path Classification with Recurrent and Convolutional Networks[C]//Thirty-Second AAAI Conference on Artificial Intelligence.Palo Alto,CA:AAAI Press,2018:354-361.
[48]YU F,LIU Q,WU S,et al.Attention-based Convolutional Ap-proach for Misinformation Identification from Massive and NoisyMicroblog Posts[J].Computers & Security,2019,83:106-121.
[49]MONTI F,FRASCA F,EYNARD D,et al.Fake News Detection on Social Media using Geometric Deep Learning[EB/OL].(2019-02-10) [2021-02-25].https://arxiv.org/pdf/1902.06673.
[50]MA J,GAO W,MITRA P,et al.Detecting rumors from micro-blogs with recurrent neural networks[C]//International Joint Conference on Artificial Intelligence.Palo Alto,CA:AAAI Press,2016:3818-3824.
[51]RUCHANSKY N,SEO S,LIU Y.CSI:A hybrid deep model for fake news detection[C]//Proceedings of the 2017 ACM on Conference on Information and Knowledge Management.New York,NY:ACM,2017:797-806.
[52]HOCHREITER S,SCHMIDHUBER J.Long Short-Term Me-mory[J].Neural Computation,1997,9(8):1735-1780.
[53]CHO K,VAN M B,GULCEHRE C,et al.Learning phrase representations using RNN encoder-decoder for statistical machine translation[EB/OL].(2014-09-03) [2021-02-25].https://ar-Xiv.org/pdf/1406.1078.
[54]ALKHODAIR S A,DING S H H,FUNG B C M,et al.Detecting breaking news rumors of emerging topics in social media[J].Information Processing & Management,2020,57(2):102018.
[55]KULA S,CHORAS' M,KOZIK R,et al.Sentiment Analysis for Fake News Detection by Means of Neural Networks[C]//Computational Science(ICCS 2020).Cham:Springer International Publishing,2020:653-666.
[56]QI P,CAO J,YANG T,et al.Exploiting Multi-domain Visual Information for Fake News Detection[C]//2019 IEEE International Conference on Data Mining (ICDM).Piscataway,NJ:IEEE,2020:8-11.
[57]UPPAL A,SACHDEVA V.Fake news detection using dis-course segment structure analysis[C]//2020 10th International Conference on Cloud Computing,Data Science & Engineering (Confluence).Piscataway,NJ:IEEE,2020:751-756.
[58]GUO H,CAO J,ZHANG Y Z,et al.Rumor detection with hie-rarchical social attention network[C]//The 27th ACM International Conference on Information and Knowledge Management.New York,NY:ACM,2018:943-951.
[59]WANG S,ZHAO X,CHEN Y,et al.Negative Influence Minimizing by Blocking Nodes in Social Networks[C]//Proceedings of the 17th AAAI Conference on Late-Breaking Developments in the Field of Artificial Intelligence.Palo Alto,CA:AAAI Press,2013:134-136.
[60]YAN R,LI D,WU W,et al.Minimizing Influence of Rumors by Blockers on Social Networks:Algorithms and Analysis[J].IEEE Transactions on Network Science and Engineering,2020,7(3):1067-1078.
[61]FAN L,LU Z,WU W,et al.Least Cost Rumor Blocking in Social Networks[C]//2013 IEEE 33rd International Conference on Distributed Computing Systems.Piscataway,NJ:IEEE,2013:540-549.
[62]FAN L,WU W,ZHAI X,et al.Maximizing rumor containment in social networks with constrained time[J].Social Network Analysis and Mining,2014,4(1):214.
[63]PHAM C V,THAI M T,DUONG H V,et al.Maximizing misinformation restriction within time and budget constraints[J].Journal of Combinatorial Optimization,2018,35(4):1202-1240.
[64]PHAM C V,PHU Q V,HOANG H X,et al.Minimum budget for misinformation blocking in online social networks[J].Journal of Combinatorial Optimization,2019,38(4):1101-1127.
[65]KIMURA M,SAITO K,MOTODA H.Minimizing the Spread of Contamination by Blocking Links in a Network[C]//Procee-dings of the Twenty-Third AAAI Conference on Artificial Intelligence.Palo Alto,CA:AAAI Press,2008:1175-1180.
[66]ZHANG H F,LI K Z,FU X C,et al.An Efficient Control Stra-tegy of Epidemic Spreading on Scale-Free Networks[J].Chinese Physics Letters,2009,26(6):068901.
[67]KIMURA M,SAITO K,MOTODA H.Solving the contamination minimization problem on networks for the linear threshold model[C]//Pacific Rim International Conference on Artificial Intelligence.Heidelberg,Berlin:Springer,2008:977-984.
[68]KUHLMAN C J,TULI G,SWARUP S,et al.Blocking simple and complex contagion by edge removal[C]//2013 IEEE 13th International Conference on Data Mining.Piscataway,NJ:IEEE,2013:399-408.
[69]YAO Q,ZHOU C,XIANG L,et al.Minimizing the negative influence by blocking links in social networks[C]//International Conference on Trustworthy Computing and Services.Heidelberg,Berlin:Springer,2014:65-73.
[70]KHALIL E B,DILKINA B,SONG L.Scalable Diffusion-Aware Optimization of Network Topology[C]//Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,NY,USA:ACM Press,2014:1226-1235.
[71]NI P K,ZHU J M.Study on the Edge Blocking Strategy of Mi-nimizing the amount of False Information Interaction in Online Social Networks[EB/OL].(2020-05-18). https://doi.org/10.16381/j.cnki.issn1003-207x.2019.Y-01.
[72]BASARAS P,KATSAROS D,TASSIULAS L.Dynamicallyblocking contagions in complex networks by cutting vital connections[C]//2015 IEEE International Conference on Communications (ICC).Piscataway,NJ:IEEE,2015:1170-1175.
[73]BUDAK C,AGRAWAL D,ELABBADI A.Limiting the Spread of Misinformation in Social Networks[C]//Proceedings of the 20th International Conference on World Wide Web.New York,NY:ACM Press,2011:665-674.
[74]LI S,ZHU Y,LI D,et al.Rumor restriction in Online Social Networks[C]//2013 IEEE 32nd International Performance Computing and Communications Conference (IPCCC).Piscata-way,NJ:IEEE,2014:6-8.
[75]PING Y,CAO Z,ZHU H.Sybil-aware least cost rumor blocking in social networks[C]//2014 IEEE Global Communications Conference.Piscataway,NJ:IEEE,2014:692-697.
[76]ZHANG H,ZHANG H,LI X,et al.Limiting the Spread ofMisinformation While Effectively Raising Awareness in Social Networks[C]//Computational Social Networks.Cham:Springer International Publishing,2015:35-47.
[77]HE X,SONG G,CHEN W,et al.Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model[C]//Proceedings of the 2012 SIAM International Conference on Data Mining.Philadelphia,PA:SIAM,2012:463-474.
[78]YANG L,LI Z,GIUA A.Containment of rumor spread in complex social networks[J].Information Sciences,2020,506:113-130.
[79]SHANG W,LIU M,LIN W,et al.Tracing the source of news based on blockchain[C]//2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS).Piscataway,NJ:IEEE,2018:377-381.
[80]HUCKLE S,WHITE M.Fake News:A Technological Ap-proach to Proving the Origins of Content,Using Blockchains[J].Big Data,2017,5(4):356.
[81]SHAE Z,TSAI J.AI blockchain platform for trusting news[C]//2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS).Piscataway,NJ:IEEE,2019:1610-1619.
[82]BABAR A,SHUKLA A,JAGTAP N,et al.News Tracing Sys-tem Using Blockchain[J].International Journal of Engineering Applied Sciences and Technology,2020,5(2):554-562.
[83]GUEGAN D.Public blockchain versus private blockhain[J].Université Paris Panthéon-Sorbonne (Post-Print and Working Papers),HAL,2017:halshs-01524440.
[84]CHEN Q,SRIVASTAVA G,PARIZI R M,et al.An incentive-aware blockchain-based solution for internet of fake media things[J].Information Processing & Management,2020,57(6):102370.
[85]WANG J,QIAO K Y,ZHANG Z Y,et al.An improvement for combination rule in evidence theory[J].Future Generation Computer Systems,2019:1-9.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

False Information in Social Networks:Definition,Detection and Control

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WANG Jian, PENG Yu-qi, ZHAO Yu-fei, YANG Jian. Survey of Social Network Public Opinion Information Extraction Based on Deep Learning [J]. Computer Science, 2022, 49(8): 279-293.
[2]	JIANG Meng-han, LI Shao-mei, ZHENG Hong-hao, ZHANG Jian-peng. Rumor Detection Model Based on Improved Position Embedding [J]. Computer Science, 2022, 49(8): 330-335.
[3]	WEI Peng, MA Yu-liang, YUAN Ye, WU An-biao. Study on Temporal Influence Maximization Driven by User Behavior [J]. Computer Science, 2022, 49(6): 119-126.
[4]	XU Jian-min, SUN Peng, WU Shu-fang. Microblog Rumor Detection Method Based on Propagation Path Tree Kernel Learning [J]. Computer Science, 2022, 49(6): 342-349.
[5]	YU Ai-xin, FENG Xiu-fang, SUN Jing-yu. Social Trust Recommendation Algorithm Combining Item Similarity [J]. Computer Science, 2022, 49(5): 144-151.
[6]	CHANG Ya-wen, YANG Bo, GAO Yue-lin, HUANG Jing-yun. Modeling and Analysis of WeChat Official Account Information Dissemination Based on SEIR [J]. Computer Science, 2022, 49(4): 56-66.
[7]	ZUO Yuan-lin, GONG Yue-jiao, CHEN Wei-neng. Budget-aware Influence Maximization in Social Networks [J]. Computer Science, 2022, 49(4): 100-109.
[8]	GUO Lei, MA Ting-huai. Friend Closeness Based User Matching [J]. Computer Science, 2022, 49(3): 113-120.
[9]	SHAO Yu, CHEN Ling, LIU Wei. Maximum Likelihood-based Method for Locating Source of Negative Influence Spreading Under Independent Cascade Model [J]. Computer Science, 2022, 49(2): 204-215.
[10]	CHEN Zhi-yi, SUI Jie. DeepFM and Convolutional Neural Networks Ensembles for Multimodal Rumor Detection [J]. Computer Science, 2022, 49(1): 101-107.
[11]	TAN Qi, ZHANG Feng-li, WANG Ting, WANG Rui-jin, ZHOU Shi-jie. Social Network User Influence Evaluation Algorithm Integrating Structure Centrality [J]. Computer Science, 2021, 48(7): 124-129.
[12]	WU Guang-zhi, GUO Bin, DING Ya-san, CHENG Jia-hui, YU Zhi-wen. Cognitive Mechanisms of Fake News [J]. Computer Science, 2021, 48(6): 306-314.
[13]	ZHANG Ren-zhi, ZHU Yan. Malicious User Detection Method for Social Network Based on Active Learning [J]. Computer Science, 2021, 48(6): 332-337.
[14]	ZHANG Shao-qin, DU Sheng-dong, ZHANG Xiao-bo, LI Tian-rui. Social Rumor Detection Method Based on Multimodal Fusion [J]. Computer Science, 2021, 48(5): 117-123.
[15]	BAO Zhi-qiang, CHEN Wei-dong. Rumor Source Detection in Social Networks via Maximum-a-Posteriori Estimation [J]. Computer Science, 2021, 48(4): 243-248.