{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T09:47:22Z","timestamp":1767260842077,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,1,20]],"date-time":"2020-01-20T00:00:00Z","timestamp":1579478400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"AOARD","award":["19IOA078"],"award-info":[{"award-number":["19IOA078"]}]},{"name":"Australian Research Council Discovery Project","award":["DP180101985"],"award-info":[{"award-number":["DP180101985"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,1,20]]},"DOI":"10.1145\/3336191.3371821","type":"proceedings-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T19:08:16Z","timestamp":1579720096000},"page":"286-294","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["Modeling Information Cascades with Self-exciting Processes via Generalized Epidemic Models"],"prefix":"10.1145","author":[{"given":"Quyu","family":"Kong","sequence":"first","affiliation":[{"name":"Australian National University &amp; UTS &amp; Data61, CSIRO, Canberra, Australia"}]},{"given":"Marian-Andrei","family":"Rizoiu","sequence":"additional","affiliation":[{"name":"University of Technology Sydney &amp; Data61, CSIRO, Sydney, Australia"}]},{"given":"Lexing","family":"Xie","sequence":"additional","affiliation":[{"name":"Australian National University &amp; Data61, CSIRO, Canberra, Australia"}]}],"member":"320","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"volume-title":"Mathematical Epidemiology","author":"Allen Linda J. S.","key":"e_1_3_2_1_1_1","unstructured":"Linda J. S. Allen . 2008. An Introduction to Stochastic Epidemic Models . In Mathematical Epidemiology . Springer , Chapter 3. Linda J. S. Allen. 2008. An Introduction to Stochastic Epidemic Models. In Mathematical Epidemiology . Springer, Chapter 3."},{"key":"e_1_3_2_1_2_1","volume-title":"Hawkes processes in finance. Market Microstructure and Liquidity","author":"Bacry Emmanuel","year":"2015","unstructured":"Emmanuel Bacry , Iacopo Mastromatteo , and Jean-Francc ois Muzy . 2015. Hawkes processes in finance. Market Microstructure and Liquidity ( 2015 ). Emmanuel Bacry, Iacopo Mastromatteo, and Jean-Francc ois Muzy. 2015. Hawkes processes in finance. Market Microstructure and Liquidity (2015)."},{"key":"e_1_3_2_1_3_1","series-title":"Series B (Methodological)","volume-title":"Some evolutionary stochastic processes. Journal of the Royal Statistical Society","author":"Bartlett MS","year":"1949","unstructured":"MS Bartlett . 1949. Some evolutionary stochastic processes. Journal of the Royal Statistical Society . Series B (Methodological) ( 1949 ). MS Bartlett. 1949. Some evolutionary stochastic processes. Journal of the Royal Statistical Society. Series B (Methodological) (1949)."},{"volume-title":"Mathematical Epidemiology","author":"Brauer Fred","key":"e_1_3_2_1_4_1","unstructured":"Fred Brauer . 2008. An Introduction to Stochastic Epidemic Models . In Mathematical Epidemiology . Springer , Chapter 2. Fred Brauer. 2008. An Introduction to Stochastic Epidemic Models. In Mathematical Epidemiology . Springer, Chapter 2."},{"key":"e_1_3_2_1_5_1","volume-title":"Marked self-exciting point process modelling of information diffusion on Twitter. The Annals of Applied Statistics","author":"Chen Feng","year":"2018","unstructured":"Feng Chen and Wai Hong Tan . 2018. Marked self-exciting point process modelling of information diffusion on Twitter. The Annals of Applied Statistics ( 2018 ). Feng Chen and Wai Hong Tan. 2018. Marked self-exciting point process modelling of information diffusion on Twitter. The Annals of Applied Statistics (2018)."},{"volume-title":"Analysis of survival data","author":"Cox D. R.","key":"e_1_3_2_1_6_1","unstructured":"D. R. Cox and D Oakes . 1984. Analysis of survival data . Routledge . D. R. Cox and D Oakes. 1984. Analysis of survival data .Routledge."},{"volume-title":"An introduction to the theory of point processes.","author":"Daley Daryl J","key":"e_1_3_2_1_7_1","unstructured":"Daryl J Daley and David Vere-Jones . 2008. Conditional Intensities and Likelihoods . In An introduction to the theory of point processes. Vol. I . Springer , Chapter 7.2. Daryl J Daley and David Vere-Jones. 2008. Conditional Intensities and Likelihoods. In An introduction to the theory of point processes. Vol. I. Springer, Chapter 7.2."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Wanying Ding Yue Shang Lifan Guo Xiaohua Hu Rui Yan and Tingting He. 2015. Video popularity prediction by sentiment propagation via implicit network. In CIKM .  Wanying Ding Yue Shang Lifan Guo Xiaohua Hu Rui Yan and Tingting He. 2015. Video popularity prediction by sentiment propagation via implicit network. In CIKM .","DOI":"10.1145\/2806416.2806505"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Nan Du Hanjun Dai Rakshit Trivedi Utkarsh Upadhyay Manuel Gomez-Rodriguez and Le Song. 2016. Recurrent marked temporal point processes: Embedding event history to vector. In KDD. ACM.  Nan Du Hanjun Dai Rakshit Trivedi Utkarsh Upadhyay Manuel Gomez-Rodriguez and Le Song. 2016. Recurrent marked temporal point processes: Embedding event history to vector. In KDD. ACM.","DOI":"10.1145\/2939672.2939875"},{"key":"e_1_3_2_1_10_1","unstructured":"Manuel Gomez-Rodriguez David Balduzzi and Bernhard Sch\u00f6lkopf. 2011. Uncovering the temporal dynamics of diffusion networks. (2011).  Manuel Gomez-Rodriguez David Balduzzi and Bernhard Sch\u00f6lkopf. 2011. Uncovering the temporal dynamics of diffusion networks. (2011)."},{"key":"e_1_3_2_1_11_1","unstructured":"Brandon Greenwell Bradley Boehmke Jay Cunningham and GBM Developers. 2019. gbm: Generalized Boosted Regression Models . R package version 2.1.5.  Brandon Greenwell Bradley Boehmke Jay Cunningham and GBM Developers. 2019. gbm: Generalized Boosted Regression Models . R package version 2.1.5."},{"key":"e_1_3_2_1_12_1","volume-title":"Spectra of some self-exciting and mutually exciting point processes. Biometrika","author":"Hawkes Alan G","year":"1971","unstructured":"Alan G Hawkes . 1971. Spectra of some self-exciting and mutually exciting point processes. Biometrika ( 1971 ). Alan G Hawkes. 1971. Spectra of some self-exciting and mutually exciting point processes. Biometrika (1971)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2501025.2501027"},{"key":"e_1_3_2_1_14_1","volume":"201","author":"Jing How","unstructured":"How Jing and Alexander J Smola. 201 7. Neural survival recommender. In WSDM . How Jing and Alexander J Smola. 2017. Neural survival recommender. In WSDM .","journal-title":"Alexander J Smola."},{"key":"e_1_3_2_1_15_1","volume-title":"Point process models of single-neuron discharges. Journal of computational neuroscience","author":"Johnson Don H","year":"1996","unstructured":"Don H Johnson . 1996. Point process models of single-neuron discharges. Journal of computational neuroscience ( 1996 ). Don H Johnson. 1996. Point process models of single-neuron discharges. Journal of computational neuroscience (1996)."},{"key":"e_1_3_2_1_16_1","volume-title":"Disease extinction and community size: modeling the persistence of measles. Science","author":"Keeling Matthew J","year":"1997","unstructured":"Matthew J Keeling and BT Grenfell . 1997. Disease extinction and community size: modeling the persistence of measles. Science ( 1997 ). Matthew J Keeling and BT Grenfell. 1997. Disease extinction and community size: modeling the persistence of measles. Science (1997)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1927.0118"},{"key":"e_1_3_2_1_18_1","unstructured":"Masahiro Kimura Kazumi Saito and Hiroshi Motoda. 2009. Efficient Estimation of Influence Functions for SIS Model on Social Networks.. In IJCAI .  Masahiro Kimura Kazumi Saito and Hiroshi Motoda. 2009. Efficient Estimation of Influence Functions for SIS Model on Social Networks.. In IJCAI ."},{"key":"e_1_3_2_1_19_1","volume-title":"The limits of statistical significance of Hawkes processes fitted to financial data. Quantitative Finance","author":"Lallouache Mehdi","year":"2016","unstructured":"Mehdi Lallouache and Damien Challet . 2016. The limits of statistical significance of Hawkes processes fitted to financial data. Quantitative Finance ( 2016 ). Mehdi Lallouache and Damien Challet. 2016. The limits of statistical significance of Hawkes processes fitted to financial data. Quantitative Finance (2016)."},{"key":"e_1_3_2_1_20_1","volume-title":"Hawkes processes. arXiv preprint arXiv:1507.02822","author":"Laub Patrick J","year":"2015","unstructured":"Patrick J Laub , Thomas Taimre , and Philip K Pollett . 2015. Hawkes processes. arXiv preprint arXiv:1507.02822 ( 2015 ). Patrick J Laub, Thomas Taimre, and Philip K Pollett. 2015. Hawkes processes. arXiv preprint arXiv:1507.02822 (2015)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Liangda Li Hongbo Deng Jianhui Chen and Yi Chang. 2017. Learning parametric models for context-aware query auto-completion via hawkes processes. In WSDM .  Liangda Li Hongbo Deng Jianhui Chen and Yi Chang. 2017. Learning parametric models for context-aware query auto-completion via hawkes processes. In WSDM .","DOI":"10.1145\/3018661.3018698"},{"key":"e_1_3_2_1_22_1","volume-title":"Hawkes Process Kernel Structure Parametric Search with Renormalization Factors. arXiv preprint arXiv:1805.09570","author":"Lima Rafael","year":"2018","unstructured":"Rafael Lima and Jaesik Choi . 2018. Hawkes Process Kernel Structure Parametric Search with Renormalization Factors. arXiv preprint arXiv:1805.09570 ( 2018 ). Rafael Lima and Jaesik Choi. 2018. Hawkes Process Kernel Structure Parametric Search with Renormalization Factors. arXiv preprint arXiv:1805.09570 (2018)."},{"key":"e_1_3_2_1_23_1","volume":"201","author":"Martin Travis","unstructured":"Travis Martin , Jake M Hofman , Amit Sharma , Ashton Anderson , and Duncan J Watts. 201 6. Exploring limits to prediction in complex social systems. In WWW . Travis Martin, Jake M Hofman, Amit Sharma, Ashton Anderson, and Duncan J Watts. 2016. Exploring limits to prediction in complex social systems. In WWW .","journal-title":"Duncan J Watts."},{"key":"e_1_3_2_1_24_1","unstructured":"Frank J Massey Jr. 195"},{"key":"e_1_3_2_1_25_1","unstructured":"Hongyuan Mei and Jason M Eisner. 2017. The neural hawkes process: A neurally self-modulating multivariate point process. In NeurIPS .  Hongyuan Mei and Jason M Eisner. 2017. The neural hawkes process: A neurally self-modulating multivariate point process. In NeurIPS ."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Swapnil Mishra Marian-Andrei Rizoiu and Lexing Xie. 2016. Feature Driven and Point Process Approaches for Popularity Prediction. In CIKM .  Swapnil Mishra Marian-Andrei Rizoiu and Lexing Xie. 2016. Feature Driven and Point Process Approaches for Popularity Prediction. In CIKM .","DOI":"10.1145\/2983323.2983812"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Swapnil Mishra Marian-Andrei Rizoiu and Lexing Xie. 2018. Modeling Popularity in Asynchronous Social Media Streams with Recurrent Neural Networks. In ICWSM .  Swapnil Mishra Marian-Andrei Rizoiu and Lexing Xie. 2018. Modeling Popularity in Asynchronous Social Media Streams with Recurrent Neural Networks. In ICWSM .","DOI":"10.1609\/icwsm.v12i1.15030"},{"volume-title":"Networks","author":"Newman Mark","key":"e_1_3_2_1_28_1","unstructured":"Mark Newman . 2018. Epidemics on networks . In Networks . Oxford university press , Chapter 17. Mark Newman. 2018. Epidemics on networks. In Networks. Oxford university press, Chapter 17."},{"key":"e_1_3_2_1_29_1","volume-title":"The asymptotic behaviour of maximum likelihood estimators for stationary point processes. Annals of the Institute of Statistical Mathematics","author":"Ogata Yoshiko","year":"1978","unstructured":"Yoshiko Ogata . 1978. The asymptotic behaviour of maximum likelihood estimators for stationary point processes. Annals of the Institute of Statistical Mathematics ( 1978 ). Yoshiko Ogata. 1978. The asymptotic behaviour of maximum likelihood estimators for stationary point processes. Annals of the Institute of Statistical Mathematics (1978)."},{"key":"e_1_3_2_1_30_1","unstructured":"Marian-Andrei Rizoiu Timothy Graham Rui Zhang Yifei Zhang Robert Ackland and Lexing Xie. 2018a. # DebateNight: The Role and Influence of Socialbots on Twitter During the 1st 2016 US Presidential Debate. In ICWSM .  Marian-Andrei Rizoiu Timothy Graham Rui Zhang Yifei Zhang Robert Ackland and Lexing Xie. 2018a. # DebateNight: The Role and Influence of Socialbots on Twitter During the 1st 2016 US Presidential Debate. In ICWSM ."},{"key":"e_1_3_2_1_31_1","unstructured":"Marian-Andrei Rizoiu Swapnil Mishra Quyu Kong Mark Carman and Lexing Xie. 2018b. SIR-Hawkes: on the Relationship Between Epidemic Models and Hawkes Point Processes. In WWW .  Marian-Andrei Rizoiu Swapnil Mishra Quyu Kong Mark Carman and Lexing Xie. 2018b. SIR-Hawkes: on the Relationship Between Epidemic Models and Hawkes Point Processes. In WWW ."},{"key":"e_1_3_2_1_32_1","unstructured":"Marian-Andrei Rizoiu Lexing Xie Scott Sanner Manuel Cebrian Honglin Yu and Pascal Van Hentenryck. 2017. Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity. In WWW .  Marian-Andrei Rizoiu Lexing Xie Scott Sanner Manuel Cebrian Honglin Yu and Pascal Van Hentenryck. 2017. Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity. In WWW ."},{"key":"e_1_3_2_1_33_1","volume-title":"Zulma M. Cucunub\u00e1, Manuel Gomez Rodriguez, Caterina Guinovart, Kyle B. Gustafson, Kammerle Schneider, Patrick G.T. Walker, Azra C. Ghani, and Samir Bhatt.","author":"Routledge Isobel","year":"2018","unstructured":"Isobel Routledge , Jos\u00e9 Eduardo Romero Chev\u00e9 z , Zulma M. Cucunub\u00e1, Manuel Gomez Rodriguez, Caterina Guinovart, Kyle B. Gustafson, Kammerle Schneider, Patrick G.T. Walker, Azra C. Ghani, and Samir Bhatt. 2018 . Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting . Nature Communications ( 2018). Isobel Routledge, Jos\u00e9 Eduardo Romero Chev\u00e9 z, Zulma M. Cucunub\u00e1, Manuel Gomez Rodriguez, Caterina Guinovart, Kyle B. Gustafson, Kammerle Schneider, Patrick G.T. Walker, Azra C. Ghani, and Samir Bhatt. 2018. Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting . Nature Communications (2018)."},{"key":"e_1_3_2_1_34_1","volume":"201","author":"Streftaris George","unstructured":"George Streftaris and Gavin J Gibson. 201 2. Non-exponential tolerance to infection in epidemic systems-modeling, inference, and assessment. Biostatistics (2012). George Streftaris and Gavin J Gibson. 2012. Non-exponential tolerance to infection in epidemic systems-modeling, inference, and assessment. Biostatistics (2012).","journal-title":"Gavin J Gibson."},{"key":"e_1_3_2_1_35_1","unstructured":"Online supplement. 2019. Appendix: titlename. http:\/\/bit.ly\/35APWE0.  Online supplement. 2019. Appendix: titlename. http:\/\/bit.ly\/35APWE0."},{"volume-title":"Mathematical Epidemiology","author":"Yan Ping","key":"e_1_3_2_1_36_1","unstructured":"Ping Yan . 2008. Distribution Theory, Stochastic Processes and Infectious Disease Modelling . In Mathematical Epidemiology . Springer , Chapter 10. Ping Yan. 2008. Distribution Theory, Stochastic Processes and Infectious Disease Modelling. In Mathematical Epidemiology . Springer, Chapter 10."},{"key":"e_1_3_2_1_37_1","volume-title":"Arming the public with artificial intelligence to counter social bots. Human Behavior and Emerging Technologies","author":"Yang Kai-Cheng","year":"2019","unstructured":"Kai-Cheng Yang , Onur Varol , Clayton A Davis , Emilio Ferrara , Alessandro Flammini , and Filippo Menczer . 2019. Arming the public with artificial intelligence to counter social bots. Human Behavior and Emerging Technologies ( 2019 ). Kai-Cheng Yang, Onur Varol, Clayton A Davis, Emilio Ferrara, Alessandro Flammini, and Filippo Menczer. 2019. Arming the public with artificial intelligence to counter social bots. Human Behavior and Emerging Technologies (2019)."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018684"},{"key":"e_1_3_2_1_39_1","volume-title":"SIR rumor spreading model in the new media age. Physica A: Statistical Mechanics and its Applications","author":"Zhao Laijun","year":"2013","unstructured":"Laijun Zhao , Hongxin Cui , Xiaoyan Qiu , Xiaoli Wang , and Jiajia Wang . 2013. SIR rumor spreading model in the new media age. Physica A: Statistical Mechanics and its Applications ( 2013 ). Laijun Zhao, Hongxin Cui, Xiaoyan Qiu, Xiaoli Wang, and Jiajia Wang. 2013. SIR rumor spreading model in the new media age. Physica A: Statistical Mechanics and its Applications (2013)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783401"},{"key":"e_1_3_2_1_41_1","unstructured":"Ke Zhou Hongyuan Zha and Le Song. 2013. Learning triggering kernels for multi-dimensional hawkes processes. In ICML .  Ke Zhou Hongyuan Zha and Le Song. 2013. Learning triggering kernels for multi-dimensional hawkes processes. In ICML ."},{"volume-title":"Ensemble methods: foundations and algorithms","author":"Zhou Zhi-Hua","key":"e_1_3_2_1_42_1","unstructured":"Zhi-Hua Zhou . 2012. Combination Methods . In Ensemble methods: foundations and algorithms . Chapman and Hall\/CRC , Chapter 4. Zhi-Hua Zhou. 2012. Combination Methods. In Ensemble methods: foundations and algorithms. Chapman and Hall\/CRC, Chapter 4."}],"event":{"name":"WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Houston TX USA","acronym":"WSDM '20"},"container-title":["Proceedings of the 13th International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371821","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3336191.3371821","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:14Z","timestamp":1750202594000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371821"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,20]]},"references-count":42,"alternative-id":["10.1145\/3336191.3371821","10.1145\/3336191"],"URL":"https:\/\/doi.org\/10.1145\/3336191.3371821","relation":{},"subject":[],"published":{"date-parts":[[2020,1,20]]},"assertion":[{"value":"2020-01-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}