Filippo Menczer

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Filippo Menczer
Fields Cognitive science
Computer science
Institutions Indiana University Bloomington
Alma mater Sapienza University of Rome

Filippo Menczer is an American and Italian professor of informatics and computer science who is the director at the Center for Complex Networks and Systems Research,[1] a research unit of the Indiana University School of Informatics and Computing and a member lab of the Web Science Trust Network. He holds courtesy appointments in Cognitive Science and Physics and is a fellow of the Institute for Scientific Interchange in Turin, Italy. On November 20, 2013 he was named a Distinguished Scientist of the ACM and a senior research fellow of the Kinsey Institute for Research in Sex, Gender, and Reproduction.[2]

Education, career, service[edit]

Menczer holds a Laurea in physics from the Sapienza University of Rome and a PhD in computer science and cognitive science from the University of California, San Diego. He used to be an assistant professor of management sciences at the University of Iowa, and a fellow-at-large of the Santa Fe Institute. At Indiana University Bloomington since 2003, he served as division chair in the Indiana University School of Informatics and Computing in 2009-2011. Menczer has been the recipient of Fulbright, Rotary Foundation, and NATO fellowships, and a Career Award from the National Science Foundation. He holds editorial positions for the journals EPJ Data Science[3] and Network Science.[4] He has served as program or track chair for various conferences including the International World Wide Web Conference and the International ACM Conference on Hypertext and Social Media.[5] He is general chair of the ACM Web Science 2014 Conference.[6]


Menczer's research focuses on Web science, social networks, social media, social computation, Web mining, data science, distributed and intelligent Web applications, and modeling of complex information networks. He introduced the idea of topical and adaptive Web crawlers, a specialized and intelligent type of Web crawler.[7][8]

Menczer is also known for his work on social phishing,[9][10] a type of phishing attacks that leverage friendship information from social networks, yielding over 70% success rate in experiments (with Markus Jakobsson); semantic similarity measures for information and social networks;[11][12][13][14] models of complex information and social networks (with Alessandro Vespignani and others);[15][16][17][18] search engine censorship;[19][20] and search engine bias.[21][22]

Menczer's group has focused on analysis and modeling of how memes and misinformation spread through social media in domains such as the Occupy movement[23][24] and political elections,[25][26] and how to combat astroturfing[27][28][29][30][31] and detect social bots.[32] Menczer and colleagues have also advanced the understanding of information virality, and in particular the effect of the competition for our finite attention[33][34] and the prediction of what memes will go viral based on the structure of early diffusion networks.[35][36]



  1. ^ "Center for Complex Networks and Systems Research (CNetS)". Retrieved May 8, 2014. 
  2. ^ "Homepage of Filippo Menczer". Center for Complex Networks and Systems Research. Retrieved December 19, 2013. 
  3. ^ "Editorial Board". EPJ Data Science. Retrieved May 4, 2014. 
  4. ^ "Editorial Team". Network Science. Retrieved May 4, 2014. 
  5. ^ "International ACM Conference on Hypertext and Social Media". Retrieved May 4, 2014. 
  6. ^ "Web Science 2014". Retrieved May 4, 2014. 
  7. ^ Menczer, F.; G. Pant; P. Srinivasan (2004). "Topical Web Crawlers: Evaluating Adaptive Algorithms". ACM Transactions on Internet Technology. 4 (4): 378–419. doi:10.1145/1031114.1031117. 
  8. ^ Srinivasan, P.; F. Menczer; G. Pant (2005). "A General Evaluation Framework for Topical Crawlers". Information Retrieval. 8 (3): 417–447. doi:10.1007/s10791-005-6993-5. 
  9. ^ Jagatic, Tom; Nathaniel Johnson; Markus Jakobsson; Filippo Menczer (October 2007). "Social Phishing". Communications of the ACM. 50 (10): 94–100. doi:10.1145/1290958.1290968. 
  10. ^ LENZ, RYAN (July 22, 2007). "School Conducts Anti-Phishing Research". The Washington Post. 
  11. ^ Maguitman, Ana; Filippo Menczer; Heather Roinestad; Alessandro Vespignani (2005). "Algorithmic detection of semantic similarity". Proceedings of the 14th international conference on World Wide Web: 107–116. doi:10.1145/1060745.1060765. 
  12. ^ Markines, Benjamin; Ciro Cattuto; Filippo Menczer; Dominik Benz; Andreas Hotho; Gerd Stumme (2009). "Evaluating similarity measures for emergent semantics of social tagging". Proceedings of the 18th international conference on World wide web: 641–650. doi:10.1145/1526709.1526796. 
  13. ^ Menczer, F (2004). "Lexical and semantic clustering by web links". Journal of the American Society for Information Science and Technology. 55 (14): 1261–1269. doi:10.1002/asi.20081. 
  14. ^ Schifanella, Rossano; Alain Barrat; Ciro Cattuto; Benjamin Markines; Filippo Menczer (2010). "Folks in folksonomies: social link prediction from shared metadata". Proceedings of the third ACM international conference on Web search and data mining: 271–280. arXiv:1003.2281Freely accessible. doi:10.1145/1718487.1718521. 
  15. ^ Fortunato, Santo; Alessandro Flammini; Filippo Menczer (2006). "Scale-free network growth by ranking". Physical Review Letters. 96: 218701. arXiv:cond-mat/0602081Freely accessible. Bibcode:2006PhRvL..96u8701F. doi:10.1103/PhysRevLett.96.218701. 
  16. ^ Ratkiewicz, Jacob; Santo Fortunato; Alessandro Flammini; Filippo Menczer; Alessandro Vespignani (2010). "Characterizing and modeling the dynamics of online popularity". Physical Review Letters. 105: 158701. Bibcode:2010PhRvL.105o8701R. doi:10.1103/PhysRevLett.105.158701. 
  17. ^ Menczer, F (2004). "Evolution of document networks". Proc. Natl. Acad. Sci. USA. 101 (suppl. 1): 5261–5265. doi:10.1073/pnas.0307554100. 
  18. ^ Menczer, F (2002). "Growing and navigating the small world web by local content". Proc. Natl. Acad. Sci. USA. 99 (22): 14014–14019. doi:10.1073/pnas.212348399. 
  19. ^ "Researchers: Impact of censorship significant on Google, other search engine results". Network World. March 15, 2006. 
  20. ^ Meiss, Mark; Filippo Menczer (2008). "Visual comparison of search results: A censorship case study". First Monday. 13 (7). doi:10.5210/fm.v13i7.2019. 
  21. ^ Fortunato, Santo; Alessandro Flammini; Filippo Menczer; Alessandro Vespignani (2006). "Topical interests and the mitigation of search engine bias". Proc. Natl. Acad. Sci. USA. 103 (34): 12684–12689. doi:10.1073/pnas.0605525103. 
  22. ^ "Egalitarian engines". The Economist. November 17, 2005. 
  23. ^ Conover, Michael; Clayton Davis; Emilio Ferrara; Karissa McKelvey; Filippo Menczer; Alessandro Flammini (2013). "The Geospatial Characteristics of a Social Movement Communication Network". PLOS ONE. 8 (3): e55957. doi:10.1371/journal.pone.0055957. 
  24. ^ Conover, Michael; Emilio Ferrara; Filippo Menczer; Alessandro Flammini (2013). "The Digital Evolution of Occupy Wall Street". PLOS ONE. 8 (5): e64679. doi:10.1371/journal.pone.0064679. 
  25. ^ Conover, Michael; Jacob Ratkiewicz; Matthew Francisco; Bruno Gonçalves; Filippo Menczer; Alessandro Flammini (2011). "Political Polarization on Twitter". Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media]]. 
  26. ^ Conover, Michael; Bruno Gonçalves; Alessandro Flammini; Filippo Menczer (2012). "Partisan asymmetries in online political activity". EPJ Data Science. 1: 6. doi:10.1140/epjds6. 
  27. ^ Ratkiewicz, Jacob; Michael Conover; Mark Meiss; Bruno Gonçalves; Snehal Patil; Alessandro Flammini; Filippo Menczer (2011). "Truthy: mapping the spread of astroturf in microblog streams". Proceedings of the 20th international conference companion on World wide web: 249–252. arXiv:1011.3768Freely accessible. doi:10.1145/1963192.1963301. 
  28. ^ Ratkiewicz, Jacob; Michael Conover; Mark Meiss; Bruno Gonçalves; Alessandro Flammini; Filippo Menczer (2011). "Detecting and Tracking Political Abuse in Social Media". Proc. Fifth International AAAI Conference on Weblogs and Social Media. 
  29. ^ Giles, Jim (27 October 2010). "Twitter tool roots out disguised mass postings". New Scientist. 
  30. ^ Keller, Jared (November 10, 2010). "When Campaigns Manipulate Social Media". The Atlantic. 
  31. ^ Silverman, Craig (November 4, 2011). "Misinformation Propagation". Columbia Journalism Review. 
  32. ^ Urbina, Ian (August 10, 2013). "I Flirt and Tweet. Follow Me at #Socialbot.". The New York Times. 
  33. ^ Weng, L; A Flammini; A Vespignani; F Menczer (2012). "Competition among memes in a world with limited attention". Nature Scientific Reports. 2: 335. doi:10.1038/srep00335. 
  34. ^ McKenna, Phil (April 13, 2012). "Going viral on Twitter is a random act". New Scientist. 
  35. ^ Weng, Lilian; Filippo Menczer; Yong-Yeol Ahn (2013). "Virality Prediction and Community Structure in Social Networks". Nature Scientific Reports. 3: 2522. doi:10.1038/srep02522. 
  36. ^ Matson, John (December 17, 2013). "Twitter Trends Help Researchers Forecast Viral Memes". Scientific American. 
  37. ^ "OSoMe: Home". 
  38. ^ Hotz, Robert Lee (October 1, 2011). "Decoding Our Chatter". The Wall Street Journal. 
  39. ^
  40. ^ "BotOrNot by Truthy". 
  41. ^ "Scholarometer: Browser Extension and Web Service for Academic Impact Analysis". 
  42. ^ Kolowich, Steve (December 15, 2009). "Tenure-o-meter". Inside Higher Ed. 
  43. ^ Kaur, Jasleen; Diep Thi Hoang; Xiaoling Sun; Lino Possamai; Mohsen JafariAsbagh; Snehal Patil; Filippo Menczer (2012). "Scholarometer: A Social Framework for Analyzing Impact across Disciplines". PLOS ONE. 7 (9): e43235. doi:10.1371/journal.pone.0043235. 
  44. ^ Kaur, Jasleen; Filippo Radicchi; Filippo Menczer (2013). "Universality of scholarly impact metrics". Journal of Informetrics. 7 (4): 924–932. arXiv:1305.6339Freely accessible. doi:10.1016/j.joi.2013.09.002. 
  45. ^ Van Noorden, Richard (November 6, 2013). "Who is the best scientist of them all?". Nature. 
  46. ^ "GiveALink - CNetS". 
  47. ^ Institute, CNetS and The Kinsey. "Kinsey Reporter: Share and explore anonymous data about sex.". 
  48. ^ "Kinsey Reporter". Scientific American. Retrieved May 4, 2014. 
  49. ^ Healy, Melissa (February 14, 2014). "Want to dish about Valentine's Day sex? There's an app for that". Los Angeles Times. 
  50. ^ "NaN - CNetS". 

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