, Klout score: Measuring inuence across multiple social networks, IEEE Intl. Conf. on Big Data (Big Data), pp.2282-2289, 2015.

Z. Abbassi, A. Bhaskara, and V. Misra, Optimizing Display Advertising in Online Social Networks, Proc. Intl. Conf. on World Wide Web, pp.1-11, 2015.

M. Abouelhoda and M. Ghanem, String mining in bioinformatics, Scientic Data Mining and Knowledge Discovery, pp.207-247, 2009.

R. Agrawal, T. Imieliundenedski, and A. Swami, Mining association rules between sets of items in large databases, SIGMOD Rec, vol.22, issue.2, pp.207-216, 1993.

Ç. Aslay, W. Lu, F. Bonchi, A. Goyal, V. S. Laks et al., Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret, Proc. VLDB Endow, vol.8, issue.7, pp.822-833, 2015.

R. Bandari, S. Asur, and B. Huberman, The pulse of news in social media: Forecasting popularity, Proc. Intl. AAAI Conf. on Weblogs and Social Media (ICWSM), 2012.

C. Buntain and J. Golbeck, Automatically Identifying Fake News in Popular Twitter Threads, Proc. IEEE Intl. Conf. on Smart Cloud (SmartCloud), pp.208-215, 2017.

Q. Cao, H. Shen, J. Gao, B. Wei, and X. Cheng, Popularity Prediction on Social Platforms with Coupled Graph Neural Networks, Proc. ACM Intl. Conf. on Web Search and Data Mining WSDM, pp.70-78, 2020.

D. Dupuis, N. Cédric-du-mouza, G. Travers, and . Chareyron, RTIM: A Real-Time Inuence Maximization Strategy, Proc. Intl. Conf. on Web Information Systems Engineering

M. Gaurav, A. Srivastava, A. Kumar, and S. Miller, Leveraging candidate popularity on twitter to predict election outcome, Proc. Intl. Work. on Social Network Mining and Analysis, pp.1-8, 2013.

J. Han, J. Pei, B. Mortazavi-asl, Q. Chen, U. Dayal et al., Freespan: frequent pattern-projected sequential pattern mining, Proc. ACM Intl. Conf. on Knowledge Discovery and Data mining (KDD), pp.355-359, 2000.

J. Han, J. Pei, B. Mortazavi-asl, H. Pinto, Q. Chen et al., Prexspan: Mining sequential patterns eciently by prex-projected pattern growth, Proc. Intl. Conf. on Data Engineering (ICDE), pp.215-224, 2001.

J. Han, J. Pei, and Y. Yin, Mining frequent patterns without candidate generation, ACM sigmod record, vol.29, issue.2, pp.1-12, 2000.

L. Hong, O. Dan, and B. D. Davison, Predicting Popular Messages in Twitter, Proc. Intl. Conf. on World Wide Web (WWW), pp.57-58, 2011.

S. Hong and D. Nadler, Which candidates do the public discuss online in an election campaign?: The use of social media by 2012 presidential candidates and its impact on candidate salience, Government information quarterly, vol.29, issue.4, pp.455-461, 2012.

N. Imran, Z. Junejo, and . Al-aghbari, Using SAX representation for human action recognition, Journal of Visual Communication and Image Representation, vol.23, issue.6, pp.853-861, 2012.

A. Karami and A. Elkouri, Political Popularity Analysis in Social Media. CoRR, 2018.

D. Kempe, J. Kleinberg, and E. Tardos, Maximizing the Spread of Inuence through a Social Network, Theory of Computing, vol.11, p.43, 2015.

P. Lagree, O. Cappe, B. Cautis, and S. Maniu, Eective Large-Scale Online Inuence Maximization, pp.937-942, 2017.

H. Li, S. Sourav, A. Bhowmick, and . Sun, CASINO: Towards Conformity-aware Social Inuence Analysis in Online Social Networks

H. Li, S. Sourav, A. Bhowmick, and . Sun, CINEMA: conformity-aware greedy algorithm for inuence maximization in online social networks, vol.323, 2013.

J. Lin, E. Keogh, L. Wei, and S. Lonardi, Experiencing SAX: a novel symbolic representation of time series, Data Mining and Knowledge Discovery, vol.15, issue.2, pp.107-144, 2007.

W. Litwin, Linear Hashing: A New Tool for File and Table Addressing. In Intl Conf. on Very Large Data Bases (VLDB), pp.212-223, 1980.

S. Petrovic, M. Osborne, and V. Lavrenko, Rt to Win! Predicting Message Propagation in Twitter, Proc. Intl. AAAI Conf. on Weblogs and Social Media (ICWSM), 2011.

R. Srikant, Fast algorithms for mining association rules and sequential patterns, 1996.

G. Szabo, A. Bernardo, and . Huberman, Predicting the popularity of online content, Communications of the ACM, vol.53, issue.8, pp.80-88, 2010.

J. Weng, E. Lim, J. Jiang, and Q. He, TwitterRank: nding topicsensitive inuential twitterers. page 261, 2010.

Y. Yamaguchi, T. Takahashi, T. Amagasa, and H. Kitagawa, TURank: Twitter User Ranking Based on User-Tweet Graph Analysis, Intl. Conf. on Web Information Systems Engineering (WISE), pp.240-253, 2010.

J. Mohammed and . Zaki, Spade: An ecient algorithm for mining frequent sequences, Machine learning, vol.42, issue.1-2, pp.31-60, 2001.

R. Tauhid-r-zaman, J. Herbrich, D. Van-gael, and . Stern, Predicting information spreading in twitter, Proc. Intl. Work. on Computational Cocial Science and the Wisdom of Crowds, vol.104, pp.17599-601, 2010.

Z. Zhao, J. Zhao, Y. Sano, O. Levy, H. Takayasu et al., Fake News Propagates Dierently from Real News even at Early Stages of spreading, EPJ Data Sci, vol.9, issue.1, p.7, 2020.