View source for Biography:Filippo Menczer

{{Short description|American and Italian computer scientist}}
{{Infobox scientist
| name = Filippo Menczer
| image = [[File:Filippo_Menczer.jpg | 200px]]
| birth_date = 16 May 1965
| birth_place = [[Place:Rome|Rome]]
| field = [[Cognitive science]]<br/>[[Computer science]]<br/>[[Physics:Physics|Physics]]
| workplaces = [[Organization:Indiana University Bloomington|Indiana University Bloomington]]
| alma_mater = [[Organization:Sapienza University of Rome|Sapienza University of Rome]]<br/>[[Organization:University of California, San Diego|University of California, San Diego]]
| website = {{URL|https://cnets.indiana.edu/fil/}}
}}
'''Filippo Menczer''' is an American and Italian academic. He is a University Distinguished Professor and the Luddy Professor of Informatics and Computer Science at the Luddy School of Informatics, Computing, and Engineering, [[Organization:Indiana University|Indiana University]]. Menczer is the Director of the Observatory on Social Media,<ref>{{cite web|url=https://osome.iu.edu/ |title=Observatory on Social Media (OSoMe)|accessdate=February 5, 2023}}</ref> a research center where data scientists and journalists study the role of media and technology in society and build tools to analyze and counter disinformation and manipulation on social media. Menczer holds courtesy appointments in Cognitive Science and [[Physics:Physics|Physics]], is a founding member and advisory council member of the IU Network Science Institute,<ref>{{cite web|url=https://iuni.iu.edu/ |title=IUNI|accessdate=March 18, 2019}}</ref> a former director the Center for Complex Networks and Systems Research,<ref>{{cite web|title=Center for Complex Networks and Systems Research (CNetS)|url=http://cnets.indiana.edu/|accessdate=May 8, 2014}}</ref> a senior [[Research fellow|research fellow]] of the Kinsey Institute, a fellow of the Center for Computer-Mediated Communication,<ref>{{cite web|url=https://ccmc.ils.indiana.edu/ |title=Center for Computer-Mediated Communication|accessdate=March 18, 2019}}</ref> and a former [[Social:Fellow|fellow]] of the [[Organization:Institute for Scientific Interchange|Institute for Scientific Interchange]] in [[Place:Turin|Turin]], Italy. In 2020 he was named a [[ACM Fellow|Fellow]] of the [[Organization:Association for Computing Machinery|ACM]].

==Education, career, service==
Menczer holds a [[Social:Laurea|Laurea]] in physics from the [[Organization:Sapienza University of Rome|Sapienza University of Rome]] and a PhD in [[Computer science|computer science]] and cognitive science from the [[Organization:University of California, San Diego|University of California, San Diego]]. He used to be an assistant professor of [[Management science|management science]]s at the [[Organization:University of Iowa|University of Iowa]], and a fellow-at-large of the [[Organization:Santa Fe Institute|Santa Fe Institute]]. At [[Organization:Indiana University Bloomington|Indiana University Bloomington]] since 2003, he served as division chair in the Luddy School in 2009–2011. Menczer has been the recipient of Fulbright, Rotary Foundation, and NATO fellowships, and a [[Organization:National Science Foundation CAREER Award|CAREER Award]] from the [[Organization:National Science Foundation|National Science Foundation]]. He holds editorial positions for the journals ''Network Science'',<ref>{{cite web|title=Editorial Board|url=https://www.cambridge.org/core/journals/network-science/information/editorial-board|work=Network Science|accessdate=March 18, 2019}}</ref> ''[[Physics:European Physical Journal|EPJ]] Data Science'',<ref>{{cite web|title=Editorial Board|url=https://epjdatascience.springeropen.com/about/editorial-board|work=EPJ Data Science Editorial Board|accessdate=March 18, 2019}}</ref> ''[[Biology:PeerJ|PeerJ]] Computer Science'',<ref>{{cite web|title=PeerJ Academic Editors|url=https://peerj.com/academic-boards/editors/cs/?page=14|work=PeerJ|accessdate=March 18, 2019}}</ref> and ''HKS Misinformation Review''.<ref>{{cite web|title=HKS Misinformation Review Editorial Board|url=https://misinforeview.hks.harvard.edu/editorial-board/|accessdate=February 5, 2023}}</ref> He has served as program or track chair for various conferences including The Web Conference and the ACM Conference on Hypertext and Social Media. He was general chair of the ''ACM Web Science 2014 Conference''<ref>{{cite web|title=Web Science 2014|url=http://websci14.org/|accessdate=May 4, 2014}}</ref> and general co-chair of the ''[[Netsci Conference|NetSci]] 2017 Conference''.

==Research==
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 [[Focused crawler|topical and adaptive Web crawlers]], a specialized and intelligent type of [[Web crawler]].<ref>{{cite journal|last=Menczer|first=F.|author2=G. Pant|author3=P. Srinivasan|title=Topical Web Crawlers: Evaluating Adaptive Algorithms|journal=ACM Transactions on Internet Technology|date=2004|volume=4|issue=4|pages=378–419|doi=10.1145/1031114.1031117|s2cid=5931711}}</ref><ref>{{cite journal|last=Srinivasan|first=P.|author2=F. Menczer|author3=G. Pant|title=A General Evaluation Framework for Topical Crawlers|journal=Information Retrieval|date=2005|volume=8|issue=3|pages=417–447|doi=10.1007/s10791-005-6993-5|citeseerx=10.1.1.6.1074|s2cid=5351345}}</ref>

Menczer is also known for his work on ''social [[Phishing|phishing]],''<ref>{{cite journal|last=Jagatic|first=Tom|author2=Nathaniel Johnson |author3=Markus Jakobsson |author4=Filippo Menczer |title=Social Phishing|journal=Communications of the ACM|date=October 2007|volume=50|issue=10|pages=94–100|doi=10.1145/1290958.1290968|s2cid=15077519|doi-access=free}}</ref><ref>{{cite news|last=LENZ|first=RYAN|title=School Conducts Anti-Phishing Research|url=https://www.washingtonpost.com/wp-dyn/content/article/2007/07/22/AR2007072200439.html|newspaper=The Washington Post|date=July 22, 2007}}</ref> a type of phishing attacks that leverage friendship information from social networks, yielding over 70% success rate in experiments (with Markus Jakobsson); [[Semantic similarity|semantic similarity]] measures for information and social networks;<ref>{{cite book|last=Maguitman|first=Ana|author2=Filippo Menczer|author3=Heather Roinestad |author4=Alessandro Vespignani|title=Proceedings of the 14th international conference on World Wide Web - WWW '05 |chapter=Algorithmic detection of semantic similarity |date=2005|pages=107–116|doi=10.1145/1060745.1060765|isbn=978-1595930460|s2cid=2011198}}</ref><ref>{{cite book|last=Markines|first=Benjamin|author2=Ciro Cattuto |author3=Filippo Menczer |author4=Dominik Benz |author5=Andreas Hotho|author6=Gerd Stumme|title=Proceedings of the 18th international conference on World wide web |chapter=Evaluating similarity measures for emergent semantics of social tagging |date=2009|pages=641–650|doi=10.1145/1526709.1526796|isbn=9781605584874|citeseerx=10.1.1.183.2930|s2cid=2708853}}</ref><ref>{{cite journal|last=Menczer|first=F|title=Lexical and semantic clustering by web links|journal=Journal of the American Society for Information Science and Technology|date=2004|volume=55|issue=14|pages=1261–1269|doi=10.1002/asi.20081|citeseerx=10.1.1.72.1136}}</ref><ref>{{cite book|last=Schifanella|first=Rossano|author2=Alain Barrat|author3=Ciro Cattuto|author4=Benjamin Markines|author5=Filippo Menczer|title=Proceedings of the third ACM international conference on Web search and data mining |chapter=Folks in Folksonomies |date=2010|pages=271–280|doi=10.1145/1718487.1718521|arxiv=1003.2281|isbn=9781605588896|bibcode=2010arXiv1003.2281S|s2cid=10097662}}</ref> models of complex information and [[Social:Social network|social network]]s (with Alessandro Vespignani and others);<ref>{{cite journal|last=Fortunato|first=Santo|author2=Alessandro Flammini|author3=Filippo Menczer |title=Scale-free network growth by ranking|journal=[[Physics:Physical Review Letters|Physical Review Letters]]|date=2006|volume=96|issue=21|page=218701|doi=10.1103/PhysRevLett.96.218701|arxiv=cond-mat/0602081|bibcode=2006PhRvL..96u8701F|pmid=16803279|s2cid=11357370}}</ref><ref>{{cite journal|last=Ratkiewicz|first=Jacob|author2=Santo Fortunato|author3=Alessandro Flammini |author4=Filippo Menczer|author5=Alessandro Vespignani|title=Characterizing and modeling the dynamics of online popularity|journal=Physical Review Letters|date=2010|volume=105|issue=15|page=158701|doi=10.1103/PhysRevLett.105.158701|pmid=21230945|bibcode=2010PhRvL.105o8701R|arxiv=1005.2704|s2cid=17597814}}</ref><ref>{{cite journal|last=Menczer|first=F|title=Evolution of document networks|journal=Proc. Natl. Acad. Sci. U.S.A.|date=2004|volume=101|issue=suppl. 1|pages=5261–5265|doi=10.1073/pnas.0307554100|pmid=14747653|pmc=387305|bibcode=2004PNAS..101.5261M|doi-access=free}}</ref><ref>{{cite journal|last=Menczer|first=F|title=Growing and navigating the small world web by local content|journal=Proc. Natl. Acad. Sci. U.S.A.|date=2002|volume=99|issue=22|pages=14014–14019|doi=10.1073/pnas.212348399|pmid=12381792|pmc=137828|bibcode=2002PNAS...9914014M|doi-access=free}}</ref> [[Social:Internet censorship|search engine censorship]];<ref>{{cite news|title=Researchers: Impact of censorship significant on Google, other search engine results|url=http://www.networkworld.com/news/2006/031506-google-censorship.html|newspaper=Network World|date=March 15, 2006|access-date=May 4, 2014|archive-url=https://web.archive.org/web/20140504141128/http://www.networkworld.com/news/2006/031506-google-censorship.html|archive-date=May 4, 2014|url-status=dead}}</ref><ref>{{cite journal|last=Meiss|first=Mark|author2=Filippo Menczer|title=Visual comparison of search results: A censorship case study|journal=First Monday|date=2008|volume=13|issue=7|doi=10.5210/fm.v13i7.2019|url=http://firstmonday.org/article/view/2019/1988 |doi-access= free}}</ref> and [[Web search engine#Search engine bias|search engine bias]].<ref>{{cite journal|last=Fortunato|first=Santo|author2=Alessandro Flammini |author3=Filippo Menczer|author4=Alessandro Vespignani|title=Topical interests and the mitigation of search engine bias|journal=Proc. Natl. Acad. Sci. U.S.A.|date=2006|volume=103|issue=34|pages=12684–12689|doi=10.1073/pnas.0605525103|pmid=16901979|pmc=1568910|arxiv=cs/0511005|bibcode=2006PNAS..10312684F|doi-access=free}}</ref><ref>{{cite news|title=Egalitarian engines|url=http://www.economist.com/node/5165407|newspaper=The Economist|date=November 17, 2005}}</ref>

The group led by Menczer has analyzed and modeled how [[Philosophy:Meme|meme]]s, information, and misinformation spread through [[Social:Social media|social media]] in domains such as the [[Social:Occupy movement|Occupy movement]],<ref>{{cite journal|last=Conover|first=Michael|author2=Clayton Davis|author3=Emilio Ferrara|author4=Karissa McKelvey |author5=Filippo Menczer|author6=Alessandro Flammini|title=The Geospatial Characteristics of a Social Movement Communication Network|journal=PLOS ONE|date=2013|volume=8|issue=3|page=e55957|doi=10.1371/journal.pone.0055957|pmid=23483885|pmc=3590214|arxiv=1306.5473|bibcode=2013PLoSO...855957C|doi-access=free}}</ref><ref>{{cite journal|last=Conover|first=Michael|author2=Emilio Ferrara |author3=Filippo Menczer|author4=Alessandro Flammini|title=The Digital Evolution of Occupy Wall Street|journal=PLOS ONE|date=2013|volume=8|issue=5|page=e64679|doi=10.1371/journal.pone.0064679|pmid=23734215|pmc=3667169|arxiv=1306.5474|bibcode=2013PLoSO...864679C|doi-access=free}}</ref> the Gezi Park protests,<ref>{{cite book|last=Varol|first=Onur|author2=Emilio Ferrara|author3=Christine L. Ogan|author4=Filippo Menczer|author5=Alessandro Flammini|title=Proceedings of the 2014 ACM conference on Web science |chapter=Evolution of online user behavior during a social upheaval |pages=81–90|date=2014|doi=10.1145/2615569.2615699|isbn=9781450326223|bibcode=2014arXiv1406.7197V|arxiv=1406.7197|s2cid=6986974}}</ref> and political elections.<ref>{{cite journal|last=Conover|first=Michael|author2=Bruno Gonçalves|author3=Alessandro Flammini|author4=Filippo Menczer |title=Partisan asymmetries in online political activity|journal=EPJ Data Science|date=2012|volume=1|page=6|doi=10.1140/epjds6|bibcode=2012arXiv1205.1010C|arxiv=1205.1010|s2cid=2347930}}</ref> Data and tools from Menczer's lab have aided in finding the roots of the [[Social:Pizzagate conspiracy theory|Pizzagate conspiracy theory]]<ref>{{cite magazine |last1=Robb |first1=Amanda |title=Anatomy of a Fake News Scandal |url=https://www.rollingstone.com/politics/politics-news/anatomy-of-a-fake-news-scandal-125877/ |accessdate=18 March 2019 |magazine=Rolling Stone |date=November 16, 2017}}</ref> and the disinformation campaign targeting the White Helmets,<ref>{{cite news |last1=Solon |first1=Olivia |title=How Syria's White Helmets became victims of an online propaganda machine |url=https://www.theguardian.com/world/2017/dec/18/syria-white-helmets-conspiracy-theories |accessdate=18 March 2019 |work=The Guardian |date=18 December 2017}}</ref> and in taking down voter-suppression bots on Twitter.<ref>{{cite news |last1=Bing |first1=Christopher |title=Exclusive: Twitter deletes over 10,000 accounts that sought to discourage U.S. voting |url=https://www.reuters.com/article/us-usa-election-twitter-exclusive/exclusive-twitter-deletes-over-10000-accounts-that-sought-to-discourage-u-s-voting-idUSKCN1N72FA |accessdate=18 March 2019 |work=Reuters |date=November 2, 2018}}</ref> Menczer and coauthors have also found a link between online [[Social:COVID-19 misinformation|COVID-19 misinformation]] and vaccination hesitancy.<ref>{{cite journal |last1=Pierri |first1=Francesco |last2=Perry |first2=Brea |last3=DeVerna |first3=Matthew |last4=Yang |first4=Kai-Cheng |last5=Flammini |first5=Alessandro |last6=Menczer |first6=Filippo |last7=Bryden |first7=John |title=Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal |journal=Scientific Reports |date=2022 |volume=12 |issue=1 |page=5966 |doi=10.1038/s41598-022-10070-w |pmid=35474313 |pmc=9043199 |arxiv=2104.10635 |bibcode=2022NatSR..12.5966P |s2cid=247939732 |url=https://doi.org/10.1038/s41598-022-10070-w}}</ref>

Analysis by Menczer's team demonstrated the [[Social:Echo chamber (media)|echo-chamber]] structure of information-diffusion networks on [[Company:Twitter|Twitter]] during the 2010 United States elections.<ref>{{cite journal|last=Conover|first=Michael|author2=Jacob Ratkiewicz|author3=Matthew Francisco|author4=Bruno Gonçalves |author5=Filippo Menczer|author6=Alessandro Flammini|title=Political Polarization on Twitter|journal=Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media|date=2011|url=http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2847}}</ref> The team found that conservatives almost exclusively retweeted other conservatives while liberals retweeted other liberals. Ten years later, this work received the Test of Time Award at the 15th International AAAI Conference on Web and Social Media (ICWSM).<ref>{{cite web|url=https://www.icwsm.org/2021/#award_winners |title=ICWSM-2021 Award Winners|accessdate=February 5, 2023}}</ref> As these patterns of polarization and segregation persist,<ref>{{cite journal|last=Nikolov|first=Dimitar|author2=Alessandro Flammini|author3=Filippo Menczer|title=Right and left, partisanship predicts (asymmetric) vulnerability to misinformation|journal= Harvard Kennedy School Misinformation Review|date=2021|volume=1|issue=7|doi=10.37016/mr-2020-55|s2cid=234356375 |arxiv=2010.01462}}</ref> Menczer's team has developed a model that shows how social influence and unfollowing accelerate the emergence of online echo chambers.<ref>{{cite journal|last=Sasahara |first=Kazutoshi|author2=Wen Chen |author3=Hao Peng |author4=Giovanni Luca Ciampaglia |author5=Alessandro Flammini |author6=Filippo Menczer |title=Social Influence and Unfollowing Accelerate the Emergence of Echo Chambers |journal=Journal of Computational Social Science |date=2021|volume=4|pages=381–402 |doi=10.1007/s42001-020-00084-7|s2cid=257090517 |arxiv=1905.03919 }}</ref>

Menczer and colleagues have advanced the understanding of information virality, and in particular the prediction of what memes will go viral based on the structure of early diffusion networks<ref>{{cite journal|last=Weng|first=Lilian |author2=Filippo Menczer |author3=Yong-Yeol Ahn|title=Virality Prediction and Community Structure in Social Networks|journal=Scientific Reports|date=2013|volume=3|page=2522|doi=10.1038/srep02522|pmid=23982106 |pmc=3755286 |arxiv=1306.0158|bibcode=2013NatSR...3E2522W}}</ref><ref>{{cite news|last=Matson|first=John|title=Twitter Trends Help Researchers Forecast Viral Memes|url=http://www.scientificamerican.com/article/twitter-trends-help-researchers-forecast-viral-memes/|newspaper=Scientific American|date=December 17, 2013}}</ref> and how competition for finite attention helps explain virality patterns.<ref>{{cite journal|last=Weng|first=L|author2=A Flammini|author3=A Vespignani |author4=F Menczer |title=Competition among memes in a world with limited attention|journal=Scientific Reports|date=2012|volume=2|page=335|doi=10.1038/srep00335|pmid=22461971|pmc=3315179|bibcode=2012NatSR...2E.335W}}</ref><ref>{{cite news|last=McKenna|first=Phil|title=Going viral on Twitter is a random act|url=https://www.newscientist.com/article/dn21702-going-viral-on-twitter-is-a-random-act.html|newspaper=New Scientist|date=April 13, 2012}}</ref> In a 2018 paper in ''Nature Human Behaviour,'' Menczer and coauthors used a model to show that when agents in a social networks share information under conditions of high information load and/or low attention, the correlation between quality and popularity of information in the system decreases.<ref>{{cite journal |last1=Qiu |first1=X. |last2=F. M. Oliveira |first2=D. |last3=Sahami Shirazi |first3=A. |last4=Flammini |first4=A. |last5=Menczer |first5=F. |title=Limited individual attention and online virality of low-quality information |journal=Nature Human Behaviour |volume=1 |issue=7 |page=0132 |doi=10.1038/s41562-017-0132 |year=2017 |bibcode=2017arXiv170102694Q |arxiv=1701.02694 |s2cid=23363010 }}</ref> An erroneous analysis in the paper suggested that this effect alone would be sufficient to explain why fake news are as likely to go viral as legitimate news on Facebook. When the authors discovered the error, they retracted the paper.<ref>{{cite magazine |last1=Dancyger |first1=Lilly |title=Researchers Retract Widely Cited Fake-News Study |url=https://www.rollingstone.com/culture/culture-news/fake-news-study-retracted-777422/ |accessdate=18 March 2019 |magazine=Rolling Stone |date=10 January 2019}}</ref>

Following influential publications on the detection of [[Social:Astroturfing|astroturfing]]<ref>{{cite book|last=Ratkiewicz|first=Jacob|author2=Michael Conover|author3=Mark Meiss|author4=Bruno Gonçalves|author5=Snehal Patil|author6=Alessandro Flammini|author7=Filippo Menczer |title=Proceedings of the 20th international conference companion on World wide web |chapter=Truthy |date=2011|pages=249–252|doi=10.1145/1963192.1963301|arxiv=1011.3768|isbn=9781450306379|s2cid=1958549}}</ref><ref>{{cite journal|last=Ratkiewicz|first=Jacob|author2=Michael Conover|author3=Mark Meiss|author4=Bruno Gonçalves |author5=Alessandro Flammini|author6=Filippo Menczer|title=Detecting and Tracking Political Abuse in Social Media|journal=Proc. Fifth International AAAI Conference on Weblogs and Social Media|date=2011|url=http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2850}}</ref><ref>{{cite news|last=Giles|first=Jim|title=Twitter tool roots out disguised mass postings|url=https://www.newscientist.com/article/dn19649-twitter-tool-roots-out-disguised-mass-postings.html|newspaper=New Scientist|date=27 October 2010}}</ref><ref>{{cite news|last=Keller|first=Jared|title=When Campaigns Manipulate Social Media|url=https://www.theatlantic.com/politics/archive/2010/11/when-campaigns-manipulate-social-media/66351/|newspaper=The Atlantic|date=November 10, 2010}}</ref><ref>{{cite news|last=Silverman|first=Craig|title=Misinformation Propagation|url=https://www.cjr.org/behind_the_news/misinformation_propagation.php|newspaper=Columbia Journalism Review|date=November 4, 2011}}</ref> and ''[[Social:Social bot|social bot]]s'',<ref>{{cite journal |last1=Ferrara |first1=Emilio |last2=Varol |first2=Onur |last3=Davis |first3=Clayton A. |last4=Menczer |first4=Filippo |last5=Flammini |first5=Alessandro |title=The rise of social bots |journal=Comm. ACM |date=2016 |volume=59 |issue=7 |pages=96–104 |doi=10.1145/2818717 |url=https://cacm.acm.org/magazines/2016/7/204021-the-rise-of-social-bots/fulltext|arxiv=1407.5225 |s2cid=1914124 }}</ref><ref>{{cite news|last=Urbina|first=Ian|title=I Flirt and Tweet. Follow Me at #Socialbot.|url=https://www.nytimes.com/2013/08/11/sunday-review/i-flirt-and-tweet-follow-me-at-socialbot.html|newspaper=The New York Times|date=August 10, 2013}}</ref> Menczer and his team have studied the complex interplay between cognitive, social, and algorithmic factors that contribute to the vulnerability of social media platforms and people to manipulation,<ref>{{cite journal |last1=Lazer |first1=D. |last2=Baum |first2=M. |last3=Benkler |first3=Y. |last4=Berinsky |first4=A. |last5=Greenhill |first5=K. |last6=Menczer |first6=F. |display-authors=0 |title=The science of fake news |journal=Science |date=2018 |volume=359 |issue=6380 |pages=1094–1096 |doi=10.1126/science.aao2998 |bibcode=2018Sci...359.1094L |pmid=29590025 |arxiv=2307.07903 |s2cid=4410672 }}</ref><ref>{{cite news |last1=Menczer |first1=Filippo |title=Misinformation on social media: Can technology save us? |url=https://theconversation.com/misinformation-on-social-media-can-technology-save-us-69264 |accessdate=18 March 2019 |work=The Conversation |date=November 27, 2016}}</ref><ref>{{cite news |last1=Bergado |first1=Gabe |title=The Man Who Saw Fake News Coming |url=https://www.inverse.com/article/25195-fake-news-researcher-filippo-menczer-misinformation-facebook-google |accessdate=18 March 2019 |work=Inverse |date=December 14, 2016}}</ref><ref>{{cite journal |last1=Mitchell Waldrop |first1=M. |title=The genuine problem of fake news |journal=PNAS |date=November 28, 2017 |doi=10.1073/pnas.1719005114 |volume=114 |issue=48 |pages=12631–12634|pmid=29146827 |pmc=5715799 |bibcode=2017PNAS..11412631W |doi-access=free }}</ref> and focused on developing tools to counter such abuse.<ref>{{cite news |last1=Ciampaglia |first1=Giovanni Luca |last2=Menczer |first2=Filippo |title=Misinformation and biases infect social media, both intentionally and accidentally |url=https://theconversation.com/misinformation-and-biases-infect-social-media-both-intentionally-and-accidentally-97148 |accessdate=18 March 2019 |work=The Conversation |date=June 20, 2018}}</ref><ref>{{cite news |last1=Zamudio-Suaréz |first1=Fernanda |title=A Professor Once Targeted by Fake News Now Is Helping to Visualize It |url=https://www.chronicle.com/article/A-Professor-Once-Targeted-by/238742 |accessdate=18 March 2019 |work=The Chronicle of Higher Education |date=December 22, 2016}}</ref> Their bot detection tool, Botometer, was used to assess the prevalence of social bots<ref>{{cite journal |last1=Varol |first1=Onur |last2=Ferrara |first2=Emilio |last3=Davis |first3=Clayton A. |last4=Menczer |first4=Filippo |last5=Flammini |first5=Alessandro |title=Online Human-Bot Interactions: Detection, Estimation, and Characterization |journal=Proc. Intl. AAAI Conf. On Web and Social Media (ICWSM) |date=2017 |volume=11 |pages=280–289 |doi=10.1609/icwsm.v11i1.14871 |url=https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15587|bibcode=2017arXiv170303107V |arxiv=1703.03107 |s2cid=15103351 }}</ref><ref>{{cite news |last1=Chong |first1=Zoey |title=Up to 48 million Twitter accounts are bots, study says |url=https://www.cnet.com/news/new-study-says-almost-15-percent-of-twitter-accounts-are-bots/ |accessdate=18 March 2019 |work=CNET |date=March 14, 2017}}</ref> and their sharing activity.<ref>{{cite web |last1=WOJCIK |first1=STEFAN |last2=MESSING |first2=SOLOMON |last3=SMITH |first3=AARON |last4=RAINIE |first4=LEE |last5=HITLIN |first5=PAUL |title=Bots in the Twittersphere |url=http://www.pewinternet.org/2018/04/09/bots-in-the-twittersphere/ |website=Pew Research Center |accessdate=18 March 2019|date=2018-04-09 }}</ref> Their tool to visualize the spread of low-credibility content, Hoaxy,<ref>{{cite news |last1=Gershgorn |first1=Dave |title=There's a new tool to visualize how fake news is spread on Twitter |url=https://qz.com/869344/theres-a-new-tool-to-visualize-how-fake-news-is-spread-on-twitter/ |accessdate=18 March 2019 |work=Quartz |date=December 21, 2016}}</ref><ref>{{cite news |last1=Kauffman |first1=Gretel |title=Indiana University tech tool 'Hoaxy' shows how fake news spreads |url=https://www.csmonitor.com/Technology/2016/1222/Indiana-University-tech-tool-Hoaxy-shows-how-fake-news-spreads |accessdate=18 March 2019 |work=The Christian Science Monitor |date=December 22, 2016}}</ref><ref>{{cite news |last1=Skallerup Bessette |first1=Lee |title=Hoaxy Visualizes the Spread of Online News |url=https://www.chronicle.com/blogs/profhacker/hoaxy/63397 |accessdate=18 March 2019 |work=The Chronicle of Higher Education |date=January 9, 2017}}</ref><ref>{{cite news |last1=Reaney |first1=Patricia |title=U.S. university launches tool to show how fake news spreads |url=https://www.reuters.com/article/us-usa-tech-fake-idUSKBN14A2CO |accessdate=18 March 2019 |work=Reuters |date=December 21, 2016}}</ref> was used in conjunction with Botometer to reveal the key role played by social bots in spreading low-credibility content during the 2016 United States presidential election.<ref>{{cite journal |last1=Shao |first1=C. |last2=Ciampaglia |first2=G. L. |last3=Varol |first3=O. |last4=Yang |first4=K. |last5=Flammini |first5=A. |last6=Menczer |first6=F. |title=The spread of low-credibility content by social bots |journal=Nature Communications |date=2018 |volume=9 |issue=1 |page=4787 |doi=10.1038/s41467-018-06930-7 |pmid=30459415 |pmc=6246561 |bibcode=2018NatCo...9.4787S |arxiv=1707.07592 }}</ref><ref>{{cite journal |last1=Shao |first1=C. |last2=Hui |first2=P. |last3=Wang |first3=L. |last4=Jiang |first4=X. |last5=Flammini |first5=A. |last6=Menczer |first6=F. |last7=Ciampaglia |first7=G. L. |title=Anatomy of an online misinformation network |journal=PLOS ONE |date=2018 |volume=13 |issue=4 |page=e0196087 |doi=10.1371/journal.pone.0196087 |pmid=29702657 |pmc=5922526 |bibcode=2018PLoSO..1396087S |arxiv=1801.06122 |doi-access=free }}</ref><ref>{{cite news |last1=Ouellette |first1=Jennifer |title=Study: It only takes a few seconds for bots to spread misinformation |url=https://arstechnica.com/science/2018/11/study-it-only-takes-a-few-seconds-for-bots-to-spread-misinformation/ |accessdate=18 March 2019 |work=Ars Technica |date=21 November 2018}}</ref><ref>{{cite news |last1=Boyce |first1=Jasmin |title='Relatively few' Twitter bots were needed to spread misinformation and overwhelm fact checkers, study finds |url=https://www.nbcnews.com/tech/tech-news/relatively-few-twitter-bots-were-needed-spread-misinformation-overwhelm-fact-n939021 |accessdate=18 March 2019 |work=NBC News |date=November 21, 2018}}</ref><ref>{{cite news |last1=de Haldevang |first1=Max |title=Twitter could have partly blocked Russia's 2016 election attack with CAPTCHAs |url=https://qz.com/1469498/twitter-using-captchas-could-have-stymied-russias-2016-election-attack/ |accessdate=18 March 2019 |work=Quartz |date=November 20, 2018}}</ref> Menczer's team also studied perceptions of partisan political bots, finding that Republican users are more likely to confuse conservative bots with humans, whereas Democratic users are more likely to confuse conservative human users with bots.<ref>{{cite journal |last1=Yan |first1=Harry |last2=Yang |first2=Kai-Cheng |last3=Menczer |first3=Filippo |last4=Shanahan |first4=James |title=Asymmetrical Perceptions of Partisan Political Bots |journal=New Media and Society |date=2021 |volume=23 |issue=10 |pages=3016–3037 |doi=10.1177/1461444820942744 |s2cid=225633835 |url=https://doi.org/10.1177/1461444820942744}}</ref> Using bot probes on Twitter, Menczer and coauthors demonstrated a conservative political bias on the platform.<ref>{{cite journal |last1=Chen |first1=Wen |last2=Pacheco |first2=Diogo |last3=Yang |first3=Kai-Cheng |last4=Menczer |first4=Filippo |title=Neutral Bots Probe Political Bias on Social Media |journal=Nature Communications |date=2021 |volume=12 |issue=1 |page=5580 |doi=10.1038/s41467-021-25738-6 |pmid=34552073 |pmc=8458339 |arxiv=2005.08141 |bibcode=2021NatCo..12.5580C |url=https://doi.org/10.1038/s41467-021-25738-6}}</ref>

As social media have increased their countermeasures against malicious automated accounts, Menczer and coauthors have shown that coordinated campaigns by inauthentic accounts continue to threaten information integrity on social media, and developed a framework to detect these coordinated networks.<ref>{{cite conference |url=http://doi.org/10.1609/icwsm.v15i1.18075 |title=Uncovering Coordinated Networks on Social Media: Methods and Case Studies |last1=Pacheco |first1=Diogo |last2=Hui |first2=Pik-Mai |last3=Torres-Lugo |first3=Christopher |last4=Truong |first4=Bao Tran |last5=Flammini |first5=Alessandro |last6=Menczer |first6=Filippo |date= 2021 |publisher=AAAI |book-title=Proc. International AAAI Conference on Web and Social Media (ICWSM) |pages=455–466 |doi=10.1609/icwsm.v15i1.18075 |arxiv=2001.05658 }}</ref> They also demonstrated new forms of social media manipulation by which bad actors can grow influence networks<ref>{{cite conference |url=https://doi.org/10.1609/icwsm.v16i1.19354 |title=The Manufacture of Partisan Echo Chambers by Follow Train Abuse on Twitter |last1= Torres-Lugo |first1=Christopher |last2=Yang |first2= Kai-Cheng |last3=Menczer |first3=Filippo |date=2022 |publisher=AAAI |book-title=Proc. International AAAI Conference on Web and Social Media (ICWSM) |pages=1017–1028 |doi=10.1609/icwsm.v16i1.19354 |arxiv=2010.13691 }}</ref> and hide high-volume of content with which they flood the network.<ref>{{cite conference |title=Manipulating Twitter through Deletions |last1=Torres-Lugo |first1=Christopher |last2=Pote |first2=Manita |last3=Nwala |first3=Alexander |last4=Menczer |first4=Filippo |date=2022 |publisher=AAAI |book-title=Proc. International AAAI Conference on Web and Social Media (ICWSM) |pages=1029–1039 |doi=10.1609/icwsm.v16i1.19355 |doi-access=free |arxiv=2203.13893 }}</ref> 

Menczer and colleagues have shown that political audience diversity can be used as an indicator of news source reliability in algorithmic ranking.<ref>{{cite journal |last1=Bhadani |first1=Saumya |last2=Yamaya |first2=Shun |last3=Flammini |first3=Alessandro |last4=Menczer |first4=Filippo |last5=Ciampaglia |first5=Giovanni |last6=Nyhan |first6=Brendan |title=Political audience diversity and news reliability in algorithmic ranking |journal=Nature Human Behaviour |date=2022 |volume=6 |issue=4 |pages=495–505 |doi=10.1038/s41562-021-01276-5 |pmid=35115677 |s2cid=220546483 |url=https://doi.org/10.1038/s41562-021-01276-5|arxiv=2007.08078 }}</ref>

==Textbook==
The textbook ''A First Course in Network Science'' by Menczer, Fortunato, and Davis was published by {{wipe|Cambridge University Press}} in 2020.<ref>{{cite book |last1=Menczer |first1=Filippo |last2=Fortunato |first2=Santo |last3=Davis |first3=Clayton |date=2020 |title=A First Course in Network Science |url= https://cambridgeuniversitypress.github.io/FirstCourseNetworkScience/ |publisher=Cambridge University Press |isbn= 9781108471138}}</ref> The textbook has been translated into Japanese, Chinese, and Korean.

==Projects==
* Observatory on Social Media (OSoMe, pronounced ''awesome''):<ref>{{cite web|url=https://osome.iuni.iu.edu/|title=OSoMe: Home|accessdate=18 March 2019}}</ref> A research center aimed to study and visualize how information spreads online.<ref>{{cite news|last=Hotz|first=Robert Lee|title=Decoding Our Chatter|url=https://www.wsj.com/news/articles/SB10001424052970204138204576598942105167646|newspaper={{wipe|The Wall Street Journal}}|date=October 1, 2011}}</ref> Includes data and tools to visualize [[Company:Twitter|Twitter]] trends, diffusion networks, detect social bots, etc.<ref>{{cite web |title=OSoMe Tools |url=https://osome.iuni.iu.edu/tools/ |website=Observatory on Social Media |accessdate=18 March 2019}}</ref><ref>{{cite journal |last1=Davis |first1=Clayton A. |display-authors=0 |title=OSoMe: The IUNI Observatory on Social Media |journal=PeerJ Computer Science |date=2016 |volume=2 |page=e87 |doi=10.7717/peerj-cs.87 |doi-access=free |hdl=11858/00-001M-0000-002D-21B1-D |hdl-access=free }}</ref> 

* Botometer:<ref>{{cite web|url=https://botometer.osome.iu.edu/|title=Botometer|accessdate=5 February 2023}}</ref> A machine learning tool to detect social bots on [[Company:Twitter|Twitter]]. Previously known as ''BotOrNot''. Includes a public API, a social bot dataset repository, and the ''BotAmp'' tool<ref>{{cite web|url=https://botometer.osome.iu.edu/botamp/|title=BotAmp|accessdate=5 February 2023}}</ref> to assess the role of automated accounts in boosting a given topic.

* Hoaxy:<ref>{{cite web |title=Hoaxy |url=https://hoaxy.osome.iu.edu/ |website=Hoaxy |accessdate=5 February 2023}}</ref> An open-source search and network visualization tool to study the spread of narratives on [[Company:Twitter|Twitter]]. Includes a public API.

* Fakey:<ref>{{cite web |title=Fakey |url=https://fakey.osome.iu.edu/ |website=Fakey |accessdate=5 February 2023}}</ref> A mobile game for news literacy. Fakey mimics a social media news feed where you have to tell real news from fake ones.

* Scholarometer:<ref>{{cite web|url=https://scholarometer.indiana.edu|title=Scholarometer|accessdate=18 March 2019}}</ref> A social tool and API to facilitate [[Citation analysis|citation analysis]] and help evaluate the [[Citation impact|impact]] of an author's publications. By [[Social:Crowdsourcing|crowdsourcing]] discipline annotations, this [[Software:Browser extension|browser extension]] is able to provide a universal metric to compare impact across disciplines.<ref>{{cite news|last=Kolowich|first=Steve|title=Tenure-o-meter|url=http://www.insidehighered.com/news/2009/12/15/tenure|newspaper=Inside Higher Ed|date=December 15, 2009}}</ref><ref>{{cite journal|last=Kaur|first=Jasleen|author2=Diep Thi Hoang|author3=Xiaoling Sun|author4=Lino Possamai|author5=Mohsen JafariAsbagh|author6=Snehal Patil|author7=Filippo Menczer|title=Scholarometer: A Social Framework for Analyzing Impact across Disciplines|journal=PLOS ONE|date=2012|volume=7|issue=9|page=e43235|doi=10.1371/journal.pone.0043235|pmid=22984414|pmc=3440403|bibcode=2012PLoSO...743235K|doi-access=free}}</ref><ref>{{cite journal|last=Kaur|first=Jasleen|author2=Filippo Radicchi |author3=Filippo Menczer|title=Universality of scholarly impact metrics|journal=Journal of Informetrics|date=2013|volume=7|issue=4|pages=924–932|doi=10.1016/j.joi.2013.09.002|arxiv=1305.6339|bibcode=2013arXiv1305.6339K|s2cid=7415777}}</ref><ref>{{cite news|last=Van Noorden|first=Richard|title=Who is the best scientist of them all?|url=http://www.nature.com/news/who-is-the-best-scientist-of-them-all-1.14108|journal=Nature|date=November 6, 2013}}</ref>

* Kinsey Reporter:<ref>{{cite web|url=https://kinseyreporter.org/|title=Kinsey Reporter|accessdate=18 March 2019}}</ref> A global mobile survey platform to share, explore, and visualize anonymous data about sex and sexual behaviors. Developed in collaboration with the Kinsey Institute. Reports are submitted via Web or smartphone, then available for visualization or offline analysis via a public API.<ref>{{cite news|title=Kinsey Reporter|url=http://www.scientificamerican.com/citizen-science/kinsey-reporter/|accessdate=May 4, 2014|newspaper=Scientific American}}</ref><ref>{{cite news|last=Healy|first=Melissa|title=Want to dish about Valentine's Day sex? There's an app for that|url=http://www.latimes.com/science/sciencenow/la-sci-sn-valentines-sex-fantasies-app-20140214,0,6256798.story|newspaper={{wipe|Los Angeles Times}}|date=February 14, 2014}}</ref>

==References==
{{Reflist|colwidth=33em}}

==External links==


{{DEFAULTSORT:Menczer, Filippo}}
[[Category:American computer scientists]]

{{Sourceattribution|Filippo Menczer}}