Computer Science ›› 2022, Vol. 49 ›› Issue (4): 56-66.doi: 10.11896/jsjkx.210900169
• Special Issue of Social Computing Based Interdisciplinary Integration • Previous Articles Next Articles
CHANG Ya-wen, YANG Bo, GAO Yue-lin, HUANG Jing-yun
CLC Number:
[1] SURHONE L M,TIMPLEDON M T,MARSEKEN S F.Social media measurement[J].Journal of Interactive Advertising,2009,10(1):94-99. [2] Watermelon data.Ecological Trend Survey Report of Q1 public account in2021 [EB/OL].(2021-06-02) [2021-05-20].https://new.qq.com/rain/a/20210602A031YK00. [3] FANG X D.Research on Wechat Communication Mechanismand Governance[J].Modern Communication,2013,35(6):122-127. [4] WANG Y J.Exploring the communication mechanism of vertical social networks from the perspective of user dexperience-- Ta-king microblog and Wechat as examples[J].Art Panorama,2016(7):161-161. [5] LI Y Z,ZHANG M T.Today’s Massmedia[J].Electronic Technology and Information Science,2017,25(12):17-19. [6] SONG Y K,LUO B.Research on rumor Spreading Mechanism in wechat moments[J].Journal of Editorial Writing,2020(4):112-114. [7] LI Q Q.The content communication characteristics of WeChat official account [J].China Publishing Journal,2018(16):50-53. [8] CAI G C.WeChat official account’s propagation characteristics and communication advantages[J].Journalism Probe,2021(9):101-102. [9] NIE Y H,CHEN H.Content is King:Research on the influencing factors of the official Wechat communication effect of archives[J].Archives Research,2019(6):53-59. [10] LIU G,WANG X Y.The influence of the headline characteristics on the dissemination of digital media content -- Based on the empirical study of the WeChat official account of news commentary[J].Journalism & Communication Review,2020,73(6):29-39. [11] JIANG Y B,LI Y W,LYU J X,et al.Research on communication power and Operation Strategy of wechat official Account of sci-tech periodicals[J].Journal of Editing,2020(3):257-261. [12] ZENG Y L,ZHOU L,ZHANG Y Y,et al.Strategies for improving the communication power of scientific academic journals’ WeChat official accounts[J].Tianjin Science and Technology,2020,47(8):108-110. [13] DIAO Y J,HE Y S,SHENG Y X.A two-stage model of new product diffusion in social networks[J].Soft Science,2017,31(10):115-119. [14] ZHU H M,YAN X,JIN Z,et al.Influence of wechat group on knowledge transmission in organizations from the perspective of coupled network[J].Systems Engineering,2020(2):1-10. [15] XU R Z,LI H L,XING C M.Research on Information Dissemination Model for Social Networking Services[J].International Journal of Computer Science and Application,2013,2(1):1-6. [16] WANG J,ZHAO L,HUANG R.SIRaRu rumor spreading mo-del in complex networks[J].Physica A:Statistical Mechanics and Its Applications,2014,398:43-55. [17] CANNARELLA J,SPECHLER J A.Epidemiological modelingof online social network dynamics[EB/OL].http://ifcfba1356eab492549echcqv5xpvxk9oq66x0.fzzh.libproxy.ruc.edu.cn/login.aspx?direct=true&db=edsarx&AN=edsarx.1401.4208&lang=zh-cn&site=eds-live. [18] WAN Y P,ZHANG D G,REN Q H.Propagation and inhibition of online rumor with considering rumor elimination process[J].Acta Physica Sinica,2015,64(24):240501. [19] PU C,LI S,YANG X,et al.Traffic-driven SIR Epidemic Spreading in Networks[J].Phusica A:Statistical Mechanics and Its Applications,2016,446:129-137. [20] LI D,MA J.How the government’s punishment and individual’s sensitivity affect the rumor spreading in online social networks[J].Physica A:Statistical Mechanics and Its Applications,2016,469:284-292. [21] MA J,LI D,TIAN Z.Rumor spreading in online social networks by considering the bipolar social reinforcement[J].Physica A:Statistical Mechanics and Its Applications,2016,447:108-115. [22] KAZUNORI S,MASATAKA N.The mechanism of collapse of the Friendster network:What can we learn from the core structure of Friendster?[J].Social Network Analysis and Mining,2017,7(1):10. [23] NIAN F,HU C,YAO S,et al.An immunization based on node activity[J].Chaos,Solitons and Fractals,2018,107:228-233. [24] ZHU L,ZHOU X,LI Y.Global dynamics analysis and control of a rumor spreading model in online social networks[J].Physica A:Statistical Mechanics and Its Applications,2019,526:120903. [25] MATHUR A,GUPTA C P.Dynamic SEIZ in Online SocialNetworks:Epidemiological Modeling of Untrue Information[J].International Journal of Advanced Computer Science and Applications (IJACSA),2020,11(7):577-585. [26] ZHANG Y,HUA S S,ZHANG H.SCIR information transmission model based on forwarding behavior influencing factors[J].Computer engineering,2018,44(11):282-599. [27] HE P.Modeling and analysis of microblog social network information dissemination based on multi-agent[D].Qingdao:Qing-dao University,2020. [28] GAO K.Research on Network Information Propagation Basedon Node State [D].Lanzhou:Lanzhou University of Technology,2020. [29] DENG W T,LI S J,CHEN K.Research on Network Information Transmission Model of wechat[J].Journal of Guangdong Institute of Petrochemical Technology,2018,28(1):43-47. [30] MA Q E,ZHANG J.Research on communication mechanism ofWeChat public Account based on SIR Model on complex Network[J].Information Science,2018,36(7):30-35. |
[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] | 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. |
[3] | YU Ai-xin, FENG Xiu-fang, SUN Jing-yu. Social Trust Recommendation Algorithm Combining Item Similarity [J]. Computer Science, 2022, 49(5): 144-151. |
[4] | ZUO Yuan-lin, GONG Yue-jiao, CHEN Wei-neng. Budget-aware Influence Maximization in Social Networks [J]. Computer Science, 2022, 49(4): 100-109. |
[5] | GUO Lei, MA Ting-huai. Friend Closeness Based User Matching [J]. Computer Science, 2022, 49(3): 113-120. |
[6] | 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. |
[7] | 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. |
[8] | SANG Chun-yan, XU Wen, JIA Chao-long, WEN Jun-hao. Prediction of Evolution Trend of Online Public Opinion Events Based on Attention Mechanism in Social Networks [J]. Computer Science, 2021, 48(7): 118-123. |
[9] | 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. |
[10] | ZHANG Ren-zhi, ZHU Yan. Malicious User Detection Method for Social Network Based on Active Learning [J]. Computer Science, 2021, 48(6): 332-337. |
[11] | 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. |
[12] | ZHANG Shao-jie, LU Xu-dong, GUO Wei, WANG Shi-peng, HE Wei. Prevention of Dishonest Behavior in Supply-Demand Matching [J]. Computer Science, 2021, 48(4): 303-308. |
[13] | ZHANG Hao-chen, CAI Ying, XIA Hong-ke. Delivery Probability Based Routing Algorithm for Vehicular Social Network [J]. Computer Science, 2021, 48(3): 289-294. |
[14] | YUAN De-yu, CHEN Shi-cong, GAO Jian, WANG Xiao-juan. Intervention Algorithm for Distorted Information in Online Social Networks Based on Stackelberg Game [J]. Computer Science, 2021, 48(3): 313-319. |
[15] | TAN Qi, ZHANG Feng-li, ZHANG Zhi-yang, CHEN Xue-qin. Modeling Methods of Social Network User Influence [J]. Computer Science, 2021, 48(2): 76-86. |
|