* [88] Xavier Molinero, Fabián Riquelme, and Maria J. Serna.  Power indices of influence games and new centrality measures for agent societies and social networks.  In Carlos Ramos, Paulo Novais, Céline Ehrwein Nihan, and Juan M. Corchado Rodríguez, editors, Ambient Intelligence - Software and Applications - 5th International Symposium on Ambient Intelligence, ISAmI 2014, Salamanca, Spain, June 4-6, 2014, volume 291 of Advances in Intelligent Systems and Computing, pages 23–30. Springer, 2014.
  * [89] Xavier Molinero, Fabián Riquelme, and Maria J. Serna.  Cooperation through social influence.  European Journal of Operational Research, 242(3):960–974, 2015.
  * [90] Manuela Montangero and Marco Furini.  TRank: Ranking Twitter users according to specific topics.  In Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE, pages 767–772, 2015.
  * [91] Flaviano Morone and Hernán A. Makse.  Influence maximization in complex networks through optimal percolation.  Nature, 524:65–68, 2015.
  * [92] Rinkesh Nagmoti, Ankur Teredesai, and Martine De Cock.  Ranking approaches for microblog search.  In Jimmy Xiangji Huang, Irwin King, Vijay V. Raghavan, and Stefan Rueger, editors, 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010, Toronto, Canada, August 31 - September 3, 2010, Main Conference Proceedings, pages 153–157. IEEE Computer Society, 2010.
  * [93] Alan Neves, Ramon Vieira, Fernando Mourāo, and Leonardo Rocha.  Quantifying complementarity among strategies for influeners’ detection on Twitter.  Procedia Computer Science, 51:2435–2444, 2015.  International Conference On Computational Science, ICCS 2015 Computational Science at the Gates of Nature.
  * [94] Thi-Tuoi Nguyen, Tri-Thanh Nguyen, and Quang-Thuy Ha.  Applying hidden topics in ranking social update streams on Twitter.  In 2013 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, RIVF 2013, Hanoi, Vietnam, November 10-13, 2013, pages 180–185. IEEE, 2013.
  * [95] Tomoya Noro, Fei Ru, Feng Xiao, and Takehiro Tokuda.  Twitter user rank using keyword search.  In Peter Vojtás, Yasushi Kiyoki, Hannu Jaakkola, Takehiro Tokuda, and Naofumi Yoshida, editors, Information Modelling and Knowledge Bases XXIV, 22nd European-Japanese Conference on Information Modelling and Knowledge Bases (EJC 2012), Prague, Czech Republic, June, 4-9, 2012, volume 251 of Frontiers in Artificial Intelligence and Applications, pages 31–48. IOS Press, 2012.
  * [96] Elisa Omodei, Manlio De Domenico, and Alex Arenas.  Characterizing interactions in online social networks during exceptional events.  Frontiers in Physics, 3(59), 2015.
  * [97] Lucas A. Overbey, Benjamin Greco, Christopher Paribello, and Terresa Jackson.  Structure and prominence in Twitter networks centered on contentious politics.  Social Network Analysis and Mining, 3(4):1351–1378, 2013.
  * [98] Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd.  The PageRank citation ranking: Bringing order to the web.  Technical report, Stanford Digital Library, 1999.
  * [99] Aditya Pal and Scott Counts.  Identifying topical authorities in microblogs.  In Irwin King, Wolfgang Nejdl, and Hang Li, editors, Proceedings of the Forth International Conference on Web Search and Web Data Mining, WSDM 2011, Hong Kong, China, February 9-12, 2011, pages 45–54. ACM, 2011.
  * [100] Karl Pearson.  Notes on regression and inheritance in the case of two parents.  In Proceedings of the Royal Society of London, volume 58, pages 240–242, 1895.
  * [101] Sen Pei, Lev Muchnik, José S. Andrade Jr., Zhiming Zheng, and Hernán A. Makse.  Searching for superspreaders of information in real-world social media.  Scientific Reports, 4(5547), 2014.
  * [102] Florian Probst, Laura Grosswiele, and Regina Pfleger.  Who will lead and who will follow: Identifying influential users in online social networks - A critical review and future research directions.  Business & Information Systems Engineering, 5(3):179–193, 2013.
  * [103] Josep M. Pujol, Ramon Sangüesa, and Jordi Delgado.  Extracting reputation in multi agent systems by means of social network topology.  In The First International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2002, July 15-19, 2002, Bologna, Italy, Proceedings, pages 467–474. ACM, 2002.
  * [104] Hemant Purohit, Jitendra Ajmera, Sachindra Joshi, Ashish Verma, and Amit P. Sheth.  Finding influential authors in brand-page communities.  In John G. Breslin, Nicole B. Ellison, James G. Shanahan, and Zeynep Tufekci, editors, Proceedings of the Sixth International Conference on Weblogs and Social Media, Dublin, Ireland, June 4-7, 2012. The AAAI Press, 2012.
  * [105] Daniele Quercia, Jonathan Ellis, Licia Capra, and Jon Crowcroft.  In the mood for being influential on Twitter.  In PASSAT/SocialCom 2011, Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Conference on Social Computing (SocialCom), Boston, MA, USA, 9-11 Oct., 2011, pages 307–314. IEEE, 2011.
  * [106] Stefan Räbiger and Myra Spiliopoulou.  A framework for validating the merit of properties that predict the influence of a Twitter user.  Expert Systems with Applications, 42(5):2824–2834, 2015.
  * [107] Gabriela Ramírez-de-la-Rosa, Esaú Villatoro-Tello, Héctor Jiménez-Salazar, and Christian Sánchez-Sánchez.  Towards automatic detection of user influence in Twitter by means of stylistic and behavioral features.  In Alexander F. Gelbukh, Félix Castro Espinoza, and Sofía N. Galicia-Haro, editors, Human-Inspired Computing and Its Applications - 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, Tuxtla Gutiérrez, Mexico, November 16-22, 2014. Proceedings, Part I, volume 8856 of Lecture Notes in Computer Science, pages 245–256. Springer, 2014.
  * [108] Adithya Rao, Nemanja Spasojevic, Zhisheng Li, and Trevor DSouza.  Klout score: Measuring influence across multiple social networks.  In 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, October 29 - November 1, 2015, pages 2282–2289. IEEE, 2015.
  * [109] Gerasimos Razis and Ioannis Anagnostopoulos.  InfluenceTracker: Rating the impact of a Twitter account.  In Lazaros S. Iliadis, Ilias Maglogiannis, Harris Papadopoulos, Spyros Sioutas, and Christos Makris, editors, Artificial Intelligence Applications and Innovations - AIAI 2014 Workshops: CoPA, MHDW, IIVC, and MT4BD, Rhodes, Greece, September 19-21, 2014. Proceedings, volume 437 of IFIP Advances in Information and Communication Technology, pages 184–195. Springer, 2014.
  * [110] Matthew Richardson and Pedro M. Domingos.  Mining knowledge-sharing sites for viral marketing.  In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-26, 2002, Edmonton, Alberta, Canada, pages 61–70. ACM, 2002.
  * [111] Daniel M. Romero, Wojciech Galuba, Sitaram Asur, and Bernardo A. Huberman.  Influence and passivity in social media.  In Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, and Michalis Vazirgiannis, editors, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III, volume 6913 of Lecture Notes in Computer Science, pages 18–33. Springer, 2011.
  * [112] Richard B. Rothenberg, John J. Potterat, Donald E. Woodhouse, William W. Darrow, Stephen Q. Muth, and Alden S. Klovdahl.  Choosing a centrality measure: Epidemiologic correlates in the Colorado Springs study of social networks.  Social Networks, 17(3–4):273–297, 1995.
  * [113] Ahmed Sameh.  A Twitter analytic tool to measure opinion, influence and trust.  Journal of Industrial and Intelligent Information, 1(1), 2013.
  * [114] Christopher B. Schenk and Douglas C. Sicker.  Finding event-specific influencers in dynamic social networks.  In PASSAT/SocialCom 2011, Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Conference on Social Computing (SocialCom), Boston, MA, USA, 9-11 Oct., 2011, pages 501–504. IEEE, 2011.
  * [115] Javier Serrano-Puche.  Herramientas web para la medición de la influencia digital: análisis de Klout y PeerIndex.  El Profesional de la Información, 21(3), 2012.  In Spanish.
  * [116] Xianlei Shao, Chunhong Zhang, and Yang Ji.  Finding domain experts in microblogs.  In Valérie Monfort and Karl-Heinz Krempels, editors, WEBIST 2014 - Proceedings of the 10th International Conference on Web Information Systems and Technologies, Volume 2, Barcelona, Spain, 3-5 April, 2014, pages 247–254. SciTePress, 2014.
  * [117] Arlei Silva, Sara Guimarães, Wagner Meira Jr., and Mohammed Javeed Zaki.  ProfileRank: finding relevant content and influential users based on information diffusion.  In Feida Zhu, Qi He, Rong Yan, and John Yen, editors, Proceedings of the 7th Workshop on Social Network Mining and Analysis, SNAKDD 2013, Chicago, IL, USA, August 11, 2013, pages 2:1–2:9. ACM, 2013.
  * [118] Michael Sippey.  Changes coming in Version 1.1 of the Twitter API.  Twitter Blogs, August 16, 2012.
https://blog.twitter.com/2012/changes-coming-in-version-11-of-the-twitter-api.

  * [119] Jure Leskovec and Andrej Krevl.  SNAP Datasets: Stanford Large Network Dataset Collection.  June 2014.
http://snap.stanford.edu/data.

  * [120] Donal Stephen Simmie, Maria Grazia Vigliotti, and Chris Hankin.  Ranking Twitter influence by combining network centrality and influence observables in an evolutionary model.  In Kokou Yétongnon, Albert Dipanda, and Richard Chbeir, editors, Ninth International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2013, Kyoto, Japan, December 2-5, 2013, pages 491–498. IEEE Computer Society, 2013.
  * [121] Xiaodan Song, Belle L. Tseng, Ching-Yung Lin, and Ming-Ting Sun.  Personalized recommendation driven by information flow.  In Efthimis N. Efthimiadis, Susan T. Dumais, David Hawking, and Kalervo Järvelin, editors, SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, Washington, USA, August 6-11, 2006, pages 509–516. ACM, 2006.
  * [122] Charles Spearman.  The proof and measurement of association between two things.  American Journal of Psychology, 15:88–103, 1904.
  * [123] M. S. Srinivasan, Srinath Srinivasa, and Sunil Thulasidasan.  Exploring celebrity dynamics on Twitter.  In Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop, I-CARE ’13, pages 13:1–13:4. New York, NY, USA, ACM, 2013.
  * [124] M. S. Srinivasan, Srinath Srinivasa, and Sunil Thulasidasan.  A comparative study of two models for celebrity identification on Twitter.  In Srikanta Bedathur, Divesh Srivastava, and Satyanarayana R. Valluri, editors, 20th International Conference on Management of Data, COMAD 2014, Hyderabad, India, December 17-19, 2014, pages 57–65. Computer Society of India, 2014.
  * [125] Giovanni Stilo, Paola Velardi, Alberto E. Tozzi, and Francesco Gesualdo.  Predicting flu epidemics using Twitter and historical data.  In Dominik Slezak, Ah-Hwee Tan, James F. Peters, and Lars Schwabe, editors, Brain Informatics and Health - International Conference, BIH 2014, Warsaw, Poland, August 11-14, 2014, Proceedings, volume 8609 of Lecture Notes in Computer Science, pages 164–177. Springer, 2014.
  * [126] Beiming Sun and Vincent T. Y. Ng.  Identifying influential users by their postings in social networks.  In Alvin Chin, Martin Atzmueller, and Denis Helic, editors, Proceedings of the 3rd international workshop on Modeling social media, MSM 2012, Milwaukee, WI, USA, June 25, 2012, pages 1–8. ACM, 2013.
  * [127] Caihong Sun, Lu Zhang, and Qian Li.  Who are influentials on micro-blogging services: Evidence from social network analysis.  In Jae-Nam Lee, Ji-Ye Mao, and James Y. L. Thong, editors, 17th Pacific Asia Conference on Information Systems, PACIS 2013, Jeju Island, Korea, June 18-22, 2013, page 25, 2013.
  * [128] Jimeng Sun and Jie Tang.  A survey of models and algorithms for social influence analysis.  In Charu C. Aggarwal, editor, Social Network Data Analytics, pages 177–214. Springer, 2011.
  * [129] Juyup Sung, Seunghyeon Moon, and Jae-Gil Lee.  The influence in Twitter: Are they really influenced?  In Longbing Cao, Hiroshi Motoda, Jaideep Srivastava, Ee-Peng Lim, Irwin King, PhilipS Yu, Wolfgang Nejdl, Guandong Xu, Gang Li, and Ya Zhang, editors, Behavior and Social Computing, volume 8178 of Lecture Notes in Computer Science, pages 95–105. Springer International Publishing, 2013.
  * [130] Arturo Tejeda-Gómez, Miquel Sànchez-Marrè, and Josep M. Pujol.  Discovering social structures of local influence by using _tweetStimuli_.  International Journal of Computer Mathematics, 91(2):291–303, 2014.
  * [131] The Telegraph.  Average Twitter user is an an American woman with an iPhone and 208 followers.  October 11, 2012.
http://www.telegraph.co.uk/technology/news/9601327/Average-Twitter-user-is-an-
an-American-woman-with-an-iPhone-and-208-followers.html.

  * [132] Ramine Tinati, Leslie Carr, Wendy Hall, and Jonny Bentwood.  Identifying communicator roles in Twitter.  In Alain Mille, Fabien L. Gandon, Jacques Misselis, Michael Rabinovich, and Steffen Staab, editors, Proceedings of the 21st World Wide Web Conference, WWW 2012, Lyon, France, April 16-20, 2012 (Companion Volume), pages 1161–1168. ACM, 2012.
  * [133] Daniel Tunkelang.  A Twitter analog to Pagerank.  January 2009.
http://thenoisychannel.com/2009/01/13/a-twitter-analog-to-pagerank.

  * [134] Thomas W. Valente, Kathryn Coronges, Cynthia Lakon, and Elizabeth Costenbader.  How correlated are network centrality measures?  Connections (Toronto, Ont), 28(1):16–26, 2008.
  * [135] Thomas W. Valente and Robert K. Foreman.  Integration and radiality: Measuring the extent of an individual’s connectedness and reachability in a network.  Social Networks, 20(1):89–105, 1998.
  * [136] Hérico Valiati, Arlei Silva, Sara Guimarães, and Wagner Meira Jr.  Uma estratégia baseada em difusão de informação para determinação de conteúdos relevantes e usuários influentes em redes sociais.  RITA, 20(3):183–208, 2013.  In Portuguese.
  * [137] Cornelius Joost van Rijsbergen.  Information Retrieval.  Butterworth, 1979.
  * [138] Esaú Villatoro-Tello, Gabriela Ramírez-de-la-Rosa, Christian Sánchez-Sánchez, Héctor Jiménez-Salazar, Wulfrano Arturo Luna-Ramírez, and Carlos Rodríguez-Lucatero.  UAMCLyR at RepLab 2014: Author profiling task.  In Linda Cappellato, Nicola Ferro, Martin Halvey, and Wessel Kraaij, editors, Working Notes for CLEF 2014 Conference, Sheffield, UK, September 15-18, 2014., volume 1180 of CEUR Workshop Proceedings, pages 1547–1558. CEUR-WS.org, 2014.
  * [139] Dimitrios Vogiatzis.  Influential users in social networks.  In Ioannis Anagnostopoulos, Mária Bieliková, Phivos Mylonas, and Nicolas Tsapatsoulis, editors, Semantic Hyper/Multimedia Adaptation - Schemes and Applications, volume 418 of Studies in Computational Intelligence, pages 271–295. Springer, 2013.
  * [140] Stanley Wasserman and Katherine Faust.  Social network analysis: Methods and applications.  Cambridge University Press, 1994.
  * [141] Benjamin Waugh, Maldini Abdipanah, Omid Hashemi, Shaquille A. Rahman, and David M. Cook.  The influence and deception of Twitter: The authenticity of the narrative and slacktivism in the australian electoral process.  In Australian Information Warfare and Security Conference, 2013.
  * [142] Leila Weitzel, Paulo Quaresma, and José Palazzo M. de Oliveira.  Measuring node importance on Twitter microblogging.  In Dumitru Dan Burdescu, Rajendra Akerkar, and Costin Badica, editors, 2nd International Conference on Web Intelligence, Mining and Semantics, WIMS ’12, Craiova, Romania, June 6-8, 2012, pages 11:1–11:7. ACM, 2012.
  * [143] Michael J. Welch, Uri Schonfeld, Dan He, and Junghoo Cho.  Topical semantics of Twitter links.  In Irwin King, Wolfgang Nejdl, and Hang Li, editors, Proceedings of the Forth International Conference on Web Search and Web Data Mining, WSDM 2011, Hong Kong, China, February 9-12, 2011, pages 327–336. ACM, 2011.
  * [144] Jianshu Weng, Ee-Peng Lim, Jing Jiang, and Qi He.  TwitterRank: finding topic-sensitive influential twitterers.  In Brian D. Davison, Torsten Suel, Nick Craswell, and Bing Liu, editors, Proceedings of the Third International Conference on Web Search and Web Data Mining, WSDM 2010, New York, NY, USA, February 4-6, 2010, pages 261–270. ACM, 2010.
  * [145] Virginia Vassilevska Williams.  Multiplying matrices faster than coppersmith-winograd.  In Howard J. Karloff and Toniann Pitassi, editors, Proceedings of the 44th Symposium on Theory of Computing Conference, STOC 2012, New York, NY, USA, May 19 - 22, 2012, pages 887–898. ACM, 2012.
  * [146] Chunjing Xiao, Yuhong Zhang, Xue Zeng, and Yue Wu.  Predicting user influence in social media.  JNW, 8(11):2649–2655, 2013.
  * [147] Feng Xiao, Tomoya Noro, and Takehiro Tokuda.  Finding news-topic oriented influential Twitter users based on topic related hashtag community detection.  J. Web Eng., 13(5&6):405–429, 2014.
  * [148] Wei Xie, Ai Phuong Hoang, Feida Zhu, and Ee-Peng Lim.  Information vs interaction: An alternative user ranking model for social networks.  In Adam Jatowt, Ee-Peng Lim, Ying Ding, Asako Miura, Taro Tezuka, Gaël Dias, Katsumi Tanaka, Andrew J. Flanagin, and Bing Tian Dai, editors, Social Informatics - 5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013, Proceedings, volume 8238 of Lecture Notes in Computer Science, pages 227–240. Springer, 2013.
  * [149] Yuto Yamaguchi, Tsubasa Takahashi, Toshiyuki Amagasa, and Hiroyuki Kitagawa.  TURank: Twitter user ranking based on user-tweet graph analysis.  In Lei Chen, Peter Triantafillou, and Torsten Suel, editors, Web Information Systems Engineering - WISE 2010 - 11th International Conference, Hong Kong, China, December 12-14, 2010. Proceedings, volume 6488 of Lecture Notes in Computer Science, pages 240–253. Springer, 2010.
  * [150] Shaozhi Ye and Shyhtsun Felix Wu.  Measuring message propagation and social influence on Twitter.com.  International Journal Communication Networks and Distributed Systems, 11(1):59–76, 2013.
  * [151] Zibin Yin and Ya Zhang.  Measuring pair-wise social influence in microblog.  In 2012 International Conference on Privacy, Security, Risk and Trust, PASSAT 2012, and 2012 International Confernece on Social Computing, SocialCom 2012, Amsterdam, Netherlands, September 3-5, 2012, pages 502–507. IEEE, 2012.
  * [152] Jinfeng Yuan, Li Li, and Le Luo Min Huang.  Topology-based algorithm for users’ influence on specific topics in micro-blog.  Journal of Information and Computational Science, 10(8):2247–2259, 2013.
  * [153] Yanmei Zhai, Xin Li, Jialiang Chen, Xiumei Fan, and William K. Cheung.  A novel topical authority-based microblog ranking.  In Lei Chen, Yan Jia, Timos Sellis, and Guanfeng Liu, editors, Web Technologies and Applications - 16th Asia-Pacific Web Conference, APWeb 2014, Changsha, China, September 5-7, 2014. Proceedings, volume 8709 of Lecture Notes in Computer Science, pages 105–116. Springer, 2014.
  * [154] Biao Zhang, Shuai Zhong, Kunmei Wen, Ruixuan Li, and Xiwu Gu.  Finding high-influence microblog users with an improved PSO algorithm.  IJMIC, 18(4):349–356, 2013.
  * [155] Jinxue Zhang, Rui Zhang, Jingchao Sun, Yanchao Zhang, and Chi Zhang.  TrueTop: A sybil-resilient system for user influence measurement on Twitter.  CoRR, abs/1504.04663, 2015.
  * [156] Meng Zhang, Caihong Sun, and Wenhui Liu.  Identifying influential users of micro-blogging services: A dynamic action-based network approach.  In Peter B. Seddon and Shirley Gregor, editors, Pacific Asia Conference on Information Systems, PACIS 2011: Quality Research in Pacific Asia, Brisbane, Queensland, Australia, 7-11 July 2011, page 223. Queensland University of Technology, 2011.
  * [157] Kang Zhao, John Yen, Greta Greer, Baojun Qiu, Prasenjit Mitra, and Kenneth Portier.  Finding influential users of online health communities: a new metric based on sentiment influence.  Journal of the American Medical Informatics Association, 21(e2):e212–e218, 2014.
  * [158] Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee-Peng Lim, Hongfei Yan, and Xiaoming Li.  Comparing Twitter and traditional media using topic models.  In Paul D. Clough, Colum Foley, Cathal Gurrin, Gareth J. F. Jones, Wessel Kraaij, Hyowon Lee, and Vanessa Murdock, editors, Advances in Information Retrieval - 33rd European Conference on IR Research, ECIR 2011, Dublin, Ireland, April 18-21, 2011. Proceedings, volume 6611 of Lecture Notes in Computer Science, pages 338–349. Springer, 2011.
  * [159] Haiyi Zhu, Bernardo A. Huberman, and Yarun Luon.  To switch or not to switch: understanding social influence in online choices.  In Joseph A. Konstan, Ed H. Chi, and Kristina Höök, editors, CHI Conference on Human Factors in Computing Systems, CHI ’12, Austin, TX, USA - May 05 - 10, 2012, pages 2257–2266. ACM, 2012.