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Faculty Profile: Emilio Ferrara from USC Viterbi on Vimeo.

Spotlight: How Emotions Spread On Twitter from USC Viterbi on Vimeo.

The Rise of Social Bots from CACM on Vimeo.

Press Coverage

  1. Twitter Has a Serious Problem—And It’s Actually a Bigger Deal Than People Realize – Mother Jones
  2. Sleeping Beauties of Science – Scientific American
  3. Twitter Bot — or Not? – The New York Times
  4. After political Twitter bot revelation, are companies at risk? – Computer World
  5. Searching for proof of Amy – San Francisco Examiner
  6. News That 48 Million Of Twitter’s Users May Be Bots Could Impact Its Valuation – Forbes
  7. How to save Twitter, two pennies at a time – The Denver Post
  8. How Understanding Identity Can Help Avoid Fraudulent Traffic – DMNews
  9. Fake accounts scandal weighs on Twitter boss – The Times
  10. Pressure Grows on Twitter CEO Dorsey Amid Bot Scandal – The Street
  11. CMO Today: Marketers and Political Wonks Gather for SXSW – The Wall Street Journal
  12. Huge number of Twitter accounts are not operated by humans – ABC News
  13. Early Twitter investor Chris Sacca says he ‘hates’ the stock, calls bot issue ‘embarrassing’ – CNBC
  14. Up to 48 million Twitter accounts are bots, study says – CNET
  15. R u bot or not? – VICE
  16. New Machine Learning Framework Uncovers Twitter’s Vast Bot Population – VICE/Motherboard
  17. A Whopping 48 Million Twitter Accounts Are Actually Just Bots, Study Says – Tech Times
  18. 15 Percent Of Twitter Accounts May Be Bots [STUDY] – Value Walk
  19. Why the Rise of Bots is a Concern for Social Networks – Enterpreneuer
  20. Study reveals whopping 48M Twitter accounts are actually bots – CBS News
  21. Twitter is home to nearly 48 million bots, according to report – The Daily Dot
  22. As many as 48 million Twitter accounts aren’t people, says study – CNBC
  23. New Study Says 48 Million Accounts On Twitter Are Bots – We are social media
  24. Almost 48 million Twitter accounts are bots – Axios
  25. Twitter user accounts: around 15% or 48 million are bots [study] – The Vanguard
  26. Report: 48 Million Twitter Accounts Are Bots – Breitbart
  27. Rise of the TWITTERBOTS – Daily Mail
  28. 15 per cent of Twitter is bots, but not the Kardashian kind – The Inquirer
  29. 48 mn Twitter accounts are bots, says study – The Economic Times
  30. 9-15 per cent of Twitter accounts are bots, reveals study – Financial Express
  31. Nearly 48 million Twitter accounts are bots: study – Deccan herald
  32. Study: Nearly 48 Million Twitter Accounts Are Fake; Many Push Political Agendas – The Libertarian Republic
  33. As many as 48 million accounts on Twitter are actually bots, study finds – Sacramento Bee
  34. Study Reveals Roughly 48M Twitter Accounts Are Actually Bots – CBS DFW
  35. Up to 48 million Twitter accounts may be Bots – Financial Buzz
  36. Up to 15% of Twitter accounts are not real people – Blasting News
  37. Tech Bytes: Twitter is Being Invaded by Bots – WDIO Eyewitness News
  38. About 9-15% of Twitter accounts are bots: Study – The Indian Express
  39. Twitter Has Nearly 48 Million Bot Accounts, So Don’t Get Hurt By All Those Online Trolls – India Times
  40. Twitter May Have 45 Million Bots on Its Hands – Investopedia
  41. Bots run amok on Twitter – My Broadband
  42. 9-15% of Twitter accounts are bots: Study – MENA FN
  43. Up To 15 Percent Of Twitter Users Are Bots, Study Says – Vocativ
  44. 48 million active Twitter accounts could be bots – Gearbrain
  45. Study: 15% of Twitter accounts could be bots – Marketing Dive
  46. 15% of Twitter users are actually bots, study claims – MemeBurn
  47. Almost 48 million Twitter accounts are bots – Click Lancashire
  48. As many as 48 million or around 15% of Twitter accounts are bots – TechWorm
  49. Twitter Has an Overwhelming 48 Million Bot Accounts – GineersNow
  50. Data Mining Reveals the Rise of ISIS Propaganda on Twitter – MIT Technology Review
  51. Data Mining Technology Helped Analyze ISIS Rise to Power – iHLS
  52. As a conservative Twitter user sleeps, his account is hard at work – Washington Post
  53. How a Chicago man posts hundreds of pro-Trump tweets each day – Daily Herald
  54. You’ve probably been tricked by fake news and don’t know it – Science News
  55. Twitter Bots Favored Trump Leading Up to Election – U.S. News
  56. How the Bot-y Politic Influenced This Election – MIT Technology Review
  57. Facebook, Twitter & Trump – The New York Review of Books
  58. How Twitter bots played a role in electing Donald Trump – WIRED
  59. Twitter Bots Pollute Public’s Understanding of Politics – Newsweek
  60. How Twitter bots helped Donald Trump win the US presidential election – Arstechnica
  61. On Twitter, No One Knows You Are a Trump Bot – Fast Company
  62. The Algorithmic Democracy – Fast Co. Design
  63. Election 2016 Belongs to the Twitter Bots – VICE
  64. USC Study Finds Many Political Tweets Come From Fake Accounts – CACM News
  65. Almost a fifth of election chatter on Twitter comes from bots – Fusion
  66. Study reports that nearly 20% of election-related tweets were ‘algorithmically driven’ – Talking New Media
  67. How Twitter bots affected the US presidential campaign – The Conversation
  68. Advertising is driving social media-fuelled fake news and it is here to stay – The Conversation
  69. 20% of All Election Related Tweets Came From Non-Humans – Futurism
  70. Twitter Bots Dominate 2016 Presidential Election: New Study – Heavy
  71. Tracking The Election With Social Media In Real-Time: How Accurate Is It? – Heavy
  72. BOTS ‘SWAY’ ELECTION Fake tweets by social media robots could swing US Presidential election – The Sun
  73. A fifth of all US election tweets have come from bots – ABC News
  74. The Trump factor tipped to spread to Australian politics as Aussie Truthers push on social media – News
  75. There are 400,000 Bots That Just Tweet Political Views All Day – Investopedia
  76. Real, or not? USC study finds many political tweets come from fake accounts – Science Blog
  77. Software bots distort Donald Trump support on Twitter: Study – ETCIO
  78. How hackers, social bots, data analysts shaped the U.S. election – The Nation
  79. That swarm of political tweets in your feed? Many could be from bots – The Business Journals
  80. Software ‘bots’ distort Trump support on Twitter – New Vision
  81. Bots Invade Twitter, Spreads Misinformation On US Election – EconoTimes
  82. Software ‘bots’ seen skewing support for Trump on Twitter – The Japan Times
  83. US Presidential Elections 2016: Bot-generated fake tweets influencing US election outcome, says new study – Indian Express
  84. US elections 2016: Researchers show how Twitter bots are trying to influence the poll in favour of Trump – International Business Times
  85. Aliens, and the autopsy into Hillary Clinton’s political death – Toronto SUN
  86. Hillary vs Trump: Most of the election chatter online by Twitter bots, says study – Tech 2 First Post
  87. Twitter bots distort Trump support – iAfrica
  88. Social Media ‘Bots’ Working To Influence U.S. Election – CBS San Francisco
  89. Almost a fifth of election chatter on Twitter comes from bots – Full Act
  90. Software ‘bots’ distort Trump support on Twitter: study – Yahoo! News
  91. Bots Will Break 2016 US Elections Results – iTechPost
  92. Scientist Worries Robot-Generated Tweets Could Compromise The Presidential Election – Newsroom America
  93. Software ‘bots’ distort Trump support on Twitter: study –
  94. Spotlight: Fake tweets endanger integrity of U.S. presidential election – XinhuanNet
  95. New Study: Twitter Bots Amount for One-Fifth of US Election Conversation – Dispatch Weekly
  96. Are Robot generated Tweets compromising US Polls? – TechRadar India
  97. Fake tweets endanger integrity of US presidential election – Global Times
  98. Software ‘bots’ distort Trump support on Twitter: study – The Daily Star
  99. Software ‘bots’ distort Trump support on Twitter: study – News Dog
  100. Malicious Twitter bots could have profound consequences for the election – RawStory
  101. ‘Robot-generated fake tweets influencing US election outcome’ – Daily News & Analysis
  102. Sophisticated Bot-Generated Tweets Could Influence Outcome of US Presidential Election – Telegiz
  103. UIC Journal Shows ‘Bots’ Sway Political Discourse, Could Impact Election – NewsWise
  104. Bot-generated tweets could threaten integrity of 2016 US presidential election: Study – BGR
  105. Bot generated tweets influence US Presidential election polls – I4U News
  106. High percentage of robot-generated fake tweets likely to influence public opinion – NewsGram
  107. ‘Robot-generated fake tweets influencing US election outcome’ – Press Trust of India
  108. Robot-generated fake tweets influencing US election outcome: Study – IndianExpress
  109. Fake Tweets, real consequences for the election –
  110. Real, or not? USC study finds many political tweets come from fake accounts – USC News
  111. We’re in a digital world filled with lots of social bots – USC News
  112. 23 reasons to get excited about data – IBM Watson Analytics
  113. Algorithm knows when corporate money is pushing memes online – New Scientist
  114. Algorithm identifies artificially promoted Twitter memes and hashtags – The Stack
  115. La fórmula científica que te podría convertir en la próxima Cara Delevingne – Vanitatis
  116. Social Network Sleuths: Investigators Pursue Criminal Gangs Via Phone Chatter – Homeland Security Today
  117. The More You Comment Online, The Dumber Your Comments Become – Huffington Post
  118. The longer you’re on the web, the less interesting your commentary becomes – USC News
  119. Cool study, bro: Why Reddit comments degrade over time – USC Press Room
  120. On Twitter, your positive tweets are actually contagiousThe Daily Dot
  121. Happiness is contagious – USC Viterbi News
  122. Pro-Trump Twitter Bots at Center of Nevada Mystery – Wall Street Journal
  123. How Ebola Infected Twitter: When it comes to sharing online, nothing spreads like fear – Nautilus
  124. Web of lies: Is the internet making a world without truth? – New Scientist
  125. The Top 100 Big Data Experts to Follow in 2016 – Maptive
  126. How DARPA Took On the Twitter Bot Menace with One Hand Behind Its Back – MIT Technology Review
  127. The US government held a contest to identify evil propaganda robots on Facebook and Twitter – Business Insider
  128. Why you need to purge your Twitter feed of angry peopleThe Telegraph
  129. Twitter Emotions Are Contagious, Says New Study, But At Least The Positive Ones Are More So Than The Negative OnesBustle
  130. Twitter users more likely to share happiness than sadness – The Rakyat Post
  131. Twitter reacts positively to upbeat emotions, study findsUSC News
  132. Positive emotions more contagious than negative ones on
  133. On Twitter, Is the Next POTUS a Bot-US?Wall Street Journal
  134. Why Does Facebook Keep Suggesting You Friend Your Tinder Matches?Vice
  135. New data suggest social media brings out the best in us, after allQuartz
  136. Bad news travels fast but positive posts spread wideThe Straits Times
  137. Positive content has greater reachBusiness First Magazine
  138. Data Shows that Positive Content Does Better on Social MediaGood
  139. Why can’t Twitter kill its bots?Fusion
  140. The Algorithm of Instagram FashionThe Science Times
  142. Here’s how to predict next season’s breakout starsDazed
  143. Instagram Can Determine Which Models Rule the Runway at Fashion WeekStyleCaster
  144. Instagram to predict next ‘It Girl’?HLN Tv
  145. Wondering Who’ll Be This Season’s Breakout Models? Apparently There’s A Mathematical Formula For ThatGrazia Daily
  146. Study Concludes Runway Models With Hips Have a Harder Time Being It Girls – Styleite
  147. FMD Featured in Indiana University Study to Predict Popular Models for NYFWSBWire
  148. NYFW: Instagram May Be Able To Predict Fashion Week’s Top ModelsUniversity Herald
  149. Scientists Can Now Predict How Successful A Model Will BeAskMen
  150. Stylebook snapshot: Researchers study impact of Instagram on models’ successPittsburg Post Gazette
  151. VIDEO: Instagram can predict top models for New York Fashion WeekIrish Examiner
  152. America’s Next Top Model Cycle 22 Winner Predicted By Instagram? Scientists Create Algorithm That Can Do ThatiSchoolGuide
  154. Instagram Correctly Predicts 80% Of Next Top Models At Fashion EventYibada
  155. Instagram can now predict who America’s Next Top Model will beDigital Trends
  158. Instagram can help predict a model’s successRed Orbit
  163. Instagram can predict the NYFW next top model with 80 percent accuracyInferse
  164. Is Instagram the new runway for fashion?Daily O
  165. How Instagram Can Predict Next Supermodels?My Tech Bits
  167. Algorithm using Instagram data can predict upcoming top modelNorthern Californian
  168. NYFW: Instagram Could Predict The Next Top ModelUniversity Herald
  169. Instagram Can Now Be Used to Predict the Fashion World’s Next SupermodeliDigitalTimes Australia
    Instagram, Social Media, and New York Fashion WeekPioneer News
  170. Instagram Predicts Future Of Modeling PopularityPress Examiner
  171. Instagram Predicts A Model’s Future Popularity According To Social ScientistsBustle
  173. Instagram Could Be Used To Identify Popularity Level Of Modelsubergizmo
  174. Instagram will tell you industry’s next top modelNature World Report
  175. Next Year’s Fashion Trends: Indiana University Algorithm Employs Instagram Data To Predict The Next Top Models Immortal News
  176. Popularity of models can be gauged using Instagram, study showsTechienews
  179. Who will be America’s next top model? Ask InstagramCBS News
  180. This Machine-Learning Algorithm Can Predict the Next Top ModelThe Fashion Spot
  181. New York Fashion Week 2015: Can Scientists Use Instagram To Identify Budding Models?iDigitalTimes
  182. Want To Know If You Can Be A Fashion Model? There’s A Machine-Learning Algorithm For ThatTech Times
  184. Scientists Can Now Predict Top Models. Sorry, TyraYahoo! Style
  185. Scientists Figure Out a Formula to Determine Top Model SuccessRacked
  186. Can You Scientifically Predict a Model’s Success?New York Magazine
  187. Machine Learning Algorithm Predicts Which New Faces Will Make It as Fashion ModelsMIT Technology Review
  188. Machine Learning Selects World’s Next Top ModelsCommunications of the ACM
  189. Slack Is Overrun With Bots. Friendly, Wonderful BotsWIRED
  190. The science of SUPERMODELS: Researchers create algorithm that scours Instagram to find the best new talentDaily Mail UK
  191. Machine learning selects world’s next top models it News
  192. IU scientists use Instagram data to forecast top models at New York Fashion WeekIU Bloomington newsroom
  193. This new study suggests sad tweets make you sadFusion
  194. The Power Of Twitter’s Emotional Influence Focus News
  195. Emotions in Tweets Are Contagious: StudyNDTV
  196. Emotions in tweets are contagious Business Standard
  197. Emotions on Twitter are contagious, says studyDNA
  198. ‘Sleeping beauty’ papers slumber for decadesNature News
  199. Even Einstein’s Research Can Take Time to MatterNew York Times
  200. ‘Sleeping beauty’ studies ahead of their timeABC Science
  201. Like Sleeping Beauty, some research lies dormant for decades, study
  202. The Dayside : Kissed by a princePhysics Today
  203. The Sleeping Beauties of SciencePacific Standard
  204. Quando la ricerca è una “bella addormentata”Le Scienze
  205. Paper all’avanguardia: fanno il botto decenni dopo la pubblicazioneOggi Scienza
  206. ‘Sleeping Beauty’ studies don’t pay off for decadesFuturity
  207. Sleeping Beauty Research Papers Can Languish For Decades, Even For Albert Einstein – Tech Times
  208. Like Sleeping Beauty, Some Research Lies Dormant for Decades News Wise
  209. El estudio de Einstein que resucitó a los 60 años y otras bellas durmientesEl Pais
  210. ‘Sleeping Beauty’ Studies Don’t Pay Off for DecadesEpoch Times
  211. Like Sleeping Beauty, some research lies dormant for decades, IU study finds Indiana University Newsroom
  212. Bot or Not? By James GleickThe New York Review of Books
  213. Twitter’s Bot Problem: Katy Perry, Taylor Swift, Justin Bieber, Rihanna And Other Musicians Have Mostly Fake Followings International Business Times
  214. Why Fear Spreads Faster Than Facts on Social MediaHootsuite
  215. In Social Networking, ‘Weak’ Connections May Be the Most
  216. Fear, Misinformation, and Social Media Complicate Ebola FightTIME
  217. Social media can improve, muddy election campaignsPittsburgh Tribune-Review
  218. How To Spot A Social Bot On TwitterMIT Technology Review
  219. Barack Obama Is Probably a Robot, and Other Lessons from ‘Bot Or Not’
  220. Social Bots on Twitter are More Than a Minor NuisanceSocial Times
  221. An Algorithm To Identify Social Bot on Twitter Value Walk
  222. Lying, spamming and scamming on the webThe Spectator
  223. This Algorithm Tells You If A Twitter Account Is a Spam BotMashable
  224. How to Spot A Bot… or Find Out If You Sound Like OneABC News
  225. Lo strumento per distinguere bot e umani su
  226. Indiana University Will Devote $1 Million to the Study of Internet MemesThe Mary Sue
  227. The U.S. government is spending $1 million to figure out memesThe Daily Dot
  228. U.S. Military Sends Scouting Party Into the TwitterverseTIME
  229. US military studied how to influence Twitter users in Darpa-funded researchThe Guardian
  230. Twitter Inc Users Studied By US Military In Darpa-Funded ResearchValue Walk
  231. How online ‘chatbots’ are already tricking youBBC
  232. ‘Bot or Not’ App Susses Out Twitter SpambotsTom’s Guide
  233. Computer scientists develop tool for uncovering bot-controlled Twitter
  234. IU computer scientists develop tool for uncovering bot-controlled Twitter accountsIU Newsroom
  235. Criminal Gang Connections Mapped via Phone MetadataCommunications of the ACM
  236. New software can map criminal gang connectionsThe Free Press Journal
  237. Gangster science: How police use network theory to track gang membersThe Daily Dot
  238. New software can map criminal gang connectionsBusiness Standard
  239. IU researcher helps Italian police fight crimeThe Washington Times
  240. Criminal gang connections mapped via phone metadataNew Scientist
  241. Mafia Wars: How Italy’s Secret Police Use Metadata To Track Organized CrimeFast Company
  242. LogAnalysis maps the structure of gangs using phone recordsEngadget
  243. How to Detect Criminal Gangs Using Mobile Phone Data MIT Technology Review
  244. Complex networks researcher at IU fighting crime with mobile phone data IU Newsroom
  245. One Tweet if by Land Newsweek
  246. Where do Twitter trends start? Try CincinnatiThe Washington Post
  247. Study: Seattle is top Twitter trendsetter in the U.S.The Seattle Times
  248. The Top Five Trend-Setting Cities on TwitterMIT Technology Review
  249. Study Finds Cincinnati Is Major Twitter Trendsetter in U.S. CityBeat
  250. Seattle generates more nationally-trending topics on Twitter than any other U.S. city, study says GeekWire
  251. Cincinnati is leading the way on TwitterCincyBizBlog
  252. The Anatomy of the Occupy Wall Street Movement on TwitterMIT Technology Review
  253. Data dance, big data and data miningThe Why Files
  254. Cell phone data analysis dials in crime networksScience News
  255. Using statistics to catch cheats and criminalsPhysics Today
  256. Bond with the best: FaceBook vs
  257. Study: Facebook Builds Better Communities Than TwitterThe Atlantic
  258. Facebook Builds Stronger Bonds Than Twitter, Study SaysMashable
  259. Study shows similarities between Facebook and real-world communitiesLeaders West
  260. Does Facebook Really Create Stronger Bonds Than Twitter?Daily lounge
  261. Facebook Encourages Stronger Bonds Over Twitter:
  262. Facebook and Strongly Connected CommunitiesCornell University
  263. Driven by friendshipSpringerSelect
  264. Facebook is a communityScience Daily
  265. Data-Mining FacebookIdiro Technologies

Press in non-English media

  1. Bad Bot oder Mensch – das ist hier die Frage – Medien Milch (in German)
  2. Studie: Bis zu 48 Millionen Twitter-Nutzer sind in Wirklichkeit Bots – T3N (in German)
  3. Der Aufstieg der Twitter-Bots: 48 Millionen Nutzer sind nicht menschlich – Studie – Sputnik News (in German)
  4. Studie: Bis zu 48 Millionen Nutzer auf Twitter sind Bots – der Standard (in German)
  5. “Blade Runner”-Test für Twitter-Accounts: Bot oder Mensch? – der Standard (in German)
  6. Bot-Paradies Twitter – Sachsische Zeitung (in German)
  7. 15 Prozent Social Bots? – DLF24 (in German)
  8. TWITTER: IST JEDER SIEBTE USER EIN BOT? – UberGizmo (in German)
  9. Twitter: Bis zu 48 Millionen Bot-Profile – Heise (in German)
  10. Studie: Bis zu 15 Prozent aller aktiven, englischsprachigen Twitter-Konten sind Bots – Netzpolitik (in German)
  11. Automatische Erregung – Wiener Zeitung (in German)
  12. 15 por ciento de las cuentas de Twitter son ‘bots’: estudio – CNET (in Spanish)
  13. 48 de los 319 millones de usuarios activos de Twitter son bots – TIC Beat (in Spanish)
  14. 15% de las cuentas de Twitter son ‘bots’ – Merca 2.0 (in Spanish)
  15. 48 de los 319 de usuarios activos en Twitter son bots – MDZ (in Spanish)
  16. Twitter, paradis des «bots»? – Slate (in French)
  17. Twitter compterait 48 millions de comptes gérés par des robots – MeltyStyle (in French)
  18. Twitter : 48 millions de comptes sont des bots – blog du moderateur (in French)
  19. ’30 tot 50 miljoen actieve Twitter-accounts zijn bots’ – NOS (in Dutch)
  20. 48 εκατομμύρια χρήστες στο Twitter δεν είναι άνθρωποι, σύμφωνα με έρευνα Πηγή – LiFo (in Greek)
  21. 48 triệu người dùng Twitter là bot và mối nguy hại – Khoa Hoc Phattrien (in Vietnamese)
  22. Post-vérité – La revue européenne des médias et du numérique (in French)
  23. Twitter, 25 mila account dell’Isis – Pagina99 (in Italian)
  24. Trump su Twitter ha un esercito di bot – Il Post (in Italian)
  25. La violencia extrema del Dáesh en Twitter le ayudó a alzarse frente a Al Qaeda – MIT Technology Review (in Spanish)
  26. Così funziona la propaganda politica a colpi di bot su Twitter – La Stampa (in Italian)
  27. Así explica la ciencia la difusión de noticias falsas en los medios de comunicaciónEl Periodico (in Spanish)
  28. 10 conductas muy contagiosas – Muy Interesante (in Spanish)
  29. Robots behind the millions of tweets: “The integrity at danger” – Svenska Dagbladet (in Swedish)
  30. Elezioni Usa: il 19% dei tweet elettorali è prodotto da software – Repubblica (in Italian)
  31. ¿Cómo nos engañan los ‘bots’ online? – (in Spanish)
  32. El atroz encanto del terror – La Nacion (in Spanish)
  33. La bella addormentata non è una favola di Natale – Giornale dell’università di Padova (in Italian)
  34. Lo que encontramos en las redes sociales afecta cada vez más a nuestro estado de ánimoPuro Marketing (in Spanish)
  35. Tuitea la alegría, que eso se pegaPrimera Hora (in Spanish)
  36. Cómo Facebook y Twitter pueden influir en tu estado de ánimoLa Nacion (in Spanish)
  37. Study: Twitter “infects” people with positive (in Russian)
  38. La joie, un sentiment virtuellement plus partagé que la tristesse sur TwitterLe Soir (in French)
  39. La joie, plus partagée que la tristesse sur TwitterLuxemburg Wort (in French)
  40. Modelle e top model, dietro il successo c’è una formula matematicaGrazia (in Italian)
  41. Come cambia la bellezza al tempo di Instagram – La Stampa (in Italian)
  42. Buzz Mode : Instagram ou la clé du succès des mannequins selon une étude de l’université de l’IndianaMelty Fashion (in French)
  43. TOP MODEL, IL SUCCESSO È IN UN ALGORITMOLettera Donna (in Italian)
  44. Un algoritmo italiano prevede il successo delle top modelCorriere (in Italian)
  45. La scienza della “super modella”: arriva l’algoritmo per scovare nuovi talenti sui socialFanpage (in Italian)
  46. Cientistas criam algoritmo que prevê o sucesso das modelos através do InstagramVisão (in Portuguese)
  47. A computer algorithm can predict the popularity of top modelsVesti (Вести.Ru in Russian)
  48. Tomorrow: the United States develop software to predict IG supermodel accuracy rate of 80%Chinatimes (in Chinese)
  49. Likes are more important than the perfect dress size Die Welt (in German)
  50. Twitterbots manipulate political debates and marketsFuturezone (in German)
  51. Il messaggio vola su FacebookFocus (pp. 78 n. 244 – Febbraio 2013) (in Italian)
  52. Come si diffondono le conversazioni? we are social (in Italian)
  53. I confini della socializzazione: non tutto si può condividereMarketingArena (in Italian)