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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.




Tech Crunch Podcast: Technotopia 


Press Coverage

  1. Twitter Bots Distorted the 2016 Election—Including Many Likely From Russia – Mother Jones
  2. Researcher Emilio Ferrara talks about the rise of fake news and botnets – Tech Crunch
  3. These Scientists Wanted To Understand Twitter’s Bot Armies, So They Built Their Own – Fast Company / Co.Design
  4. Senator Slams Twitter’s Disclosure On Russian Meddling As ‘Inadequate On Every Level’ – Forbes
  5. Twitter’s Disclosure of Russian Activity Sparks Criticism From Lawmakers – The Wall Street Journal
  6. Twitter takes its turn in the Russian probe spotlight – Politico
  7. Twitter Says It Found 201 Russia-Linked Accounts That Aimed to Influence U.S. Election – Fox Business
  8. TWITTER STORMS – Civicist
  9. JACK DORSEY TAKES HIS TURN IN THE RUSSIA PROBE BARREL – Vanity Fair
  10. Fake News on Twitter Flooded Swing States That Helped Trump Win – Mother Jones
  11. Twitter to Testify Before Senate in Russia Probe – US News
  12. Researchers find that Twitter bots can be used for good – Tech Crunch
  13. Twitter Bots Can Encourage Decent Conduct, Not Just Fake News – News18
  14. Twitter bots for good: USC ISI study reveals how information spreads on social media – EurekAlert!
  15. Germany Election So Far Unaffected by ‘Fake News’ – Snopes
  16. Social media ‘bots’ tried to influence the U.S. election. Germany may be nextScience
  17. Computational propaganda poses challengeGlobal Times
  18. Russia’s propaganda machine amplifies alt-right – The Hill
  19. #FireMcMaster, Not Damore: Twitter Bots Are Thriving, And They’re More Lethal Than Ever – Fast Company
  20. Why didn’t Macron leaks carry more clout in the French presidential election? USC News
  21. The curious case of ‘Nicole Mincey,’ the Trump fan who may actually be a botThe Washington Post
  22. Trump Thanked A ‘Supporter’ On Twitter, Then A Mystery UnraveledA Plus
  23. Spreading fake news becomes standard practice for governments across the world – The Washington Post
  24. One in five bots sharing fake news during France’s presidential election were also involved in the United States’ – ZME Science
  25. Black-market bots, duped humans are responsible for derailing elections with fake news – ThinkProgress
  26. Study: Bots have turned Twitter into a powerful political disinformation platform – Venture Beat
  27. Fake news bots are so economical, you can use them over and over – Harvard NiemanLab
  28. Pro-Trump Twitter bots were also used to target Macron, research shows – The Verge
  29. There’s a Bit of Overlap Between Bots Trying to Manipulate American and French Elections – New York Magazine
  30. Research links pro-Trump, anti-Macron Twitter bots – The Hill
  31. The Same Twitter Bots That Helped Trump Tried to Sink Macron, Researcher Says – VICE
  32. How the Hashtag Is Changing Warfare – SIGNAL
  33. How Twitter Is Being Gamed to Feed Misinformation – New York Times
  34. ‘Something fishy’ is going on with Trump’s twitter account, researchers say – Washington Post
  35. Inside Russia’s Social Media War on America – TIME (cover story)
  36. The Twitter Bots Who Tried to Steal France – Daily Beast
  37. When Facebook and Instagram Think You’re Depressed – VICE
  38. Twitter Has a Serious Problem—And It’s Actually a Bigger Deal Than People Realize – Mother Jones
  39. Sleeping Beauties of Science – Scientific American
  40. Twitter Bot — or Not? – The New York Times
  41. After political Twitter bot revelation, are companies at risk? – Computer World
  42. Searching for proof of Amy – San Francisco Examiner
  43. News That 48 Million Of Twitter’s Users May Be Bots Could Impact Its Valuation – Forbes
  44. How to save Twitter, two pennies at a time – The Denver Post
  45. How Understanding Identity Can Help Avoid Fraudulent Traffic – DMNews
  46. Fake accounts scandal weighs on Twitter boss – The Times
  47. Pressure Grows on Twitter CEO Dorsey Amid Bot Scandal – The Street
  48. CMO Today: Marketers and Political Wonks Gather for SXSW – The Wall Street Journal
  49. Huge number of Twitter accounts are not operated by humans – ABC News
  50. Early Twitter investor Chris Sacca says he ‘hates’ the stock, calls bot issue ‘embarrassing’ – CNBC
  51. Up to 48 million Twitter accounts are bots, study says – CNET
  52. R u bot or not? – VICE
  53. New Machine Learning Framework Uncovers Twitter’s Vast Bot Population – VICE/Motherboard
  54. A Whopping 48 Million Twitter Accounts Are Actually Just Bots, Study Says – Tech Times
  55. 15 Percent Of Twitter Accounts May Be Bots [STUDY] – Value Walk
  56. Why the Rise of Bots is a Concern for Social Networks – Enterpreneuer
  57. Study reveals whopping 48M Twitter accounts are actually bots – CBS News
  58. Twitter is home to nearly 48 million bots, according to report – The Daily Dot
  59. As many as 48 million Twitter accounts aren’t people, says study – CNBC
  60. New Study Says 48 Million Accounts On Twitter Are Bots – We are social media
  61. Almost 48 million Twitter accounts are bots – Axios
  62. Twitter user accounts: around 15% or 48 million are bots [study] – The Vanguard
  63. Report: 48 Million Twitter Accounts Are Bots – Breitbart
  64. Rise of the TWITTERBOTS – Daily Mail
  65. 15 per cent of Twitter is bots, but not the Kardashian kind – The Inquirer
  66. 48 mn Twitter accounts are bots, says study – The Economic Times
  67. 9-15 per cent of Twitter accounts are bots, reveals study – Financial Express
  68. Nearly 48 million Twitter accounts are bots: study – Deccan herald
  69. Study: Nearly 48 Million Twitter Accounts Are Fake; Many Push Political Agendas – The Libertarian Republic
  70. As many as 48 million accounts on Twitter are actually bots, study finds – Sacramento Bee
  71. Study Reveals Roughly 48M Twitter Accounts Are Actually Bots – CBS DFW
  72. Up to 48 million Twitter accounts may be Bots – Financial Buzz
  73. Up to 15% of Twitter accounts are not real people – Blasting News
  74. Tech Bytes: Twitter is Being Invaded by Bots – WDIO Eyewitness News
  75. About 9-15% of Twitter accounts are bots: Study – The Indian Express
  76. Twitter Has Nearly 48 Million Bot Accounts, So Don’t Get Hurt By All Those Online Trolls – India Times
  77. Twitter May Have 45 Million Bots on Its Hands – Investopedia
  78. Bots run amok on Twitter – My Broadband
  79. 9-15% of Twitter accounts are bots: Study – MENA FN
  80. Up To 15 Percent Of Twitter Users Are Bots, Study Says – Vocativ
  81. 48 million active Twitter accounts could be bots – Gearbrain
  82. Study: 15% of Twitter accounts could be bots – Marketing Dive
  83. 15% of Twitter users are actually bots, study claims – MemeBurn
  84. Almost 48 million Twitter accounts are bots – Click Lancashire
  85. As many as 48 million or around 15% of Twitter accounts are bots – TechWorm
  86. Twitter Has an Overwhelming 48 Million Bot Accounts – GineersNow
  87. Data Mining Reveals the Rise of ISIS Propaganda on Twitter – MIT Technology Review
  88. Data Mining Technology Helped Analyze ISIS Rise to Power – iHLS
  89. As a conservative Twitter user sleeps, his account is hard at work – Washington Post
  90. How a Chicago man posts hundreds of pro-Trump tweets each day – Daily Herald
  91. You’ve probably been tricked by fake news and don’t know it – Science News
  92. Twitter Bots Favored Trump Leading Up to Election – U.S. News
  93. How the Bot-y Politic Influenced This Election – MIT Technology Review
  94. Facebook, Twitter & Trump – The New York Review of Books
  95. How Twitter bots played a role in electing Donald Trump – WIRED
  96. Twitter Bots Pollute Public’s Understanding of Politics – Newsweek
  97. How Twitter bots helped Donald Trump win the US presidential election – Arstechnica
  98. On Twitter, No One Knows You Are a Trump Bot – Fast Company
  99. The Algorithmic Democracy – Fast Co. Design
  100. Election 2016 Belongs to the Twitter Bots – VICE
  101. USC Study Finds Many Political Tweets Come From Fake Accounts – CACM News
  102. Almost a fifth of election chatter on Twitter comes from bots – Fusion
  103. Study reports that nearly 20% of election-related tweets were ‘algorithmically driven’ – Talking New Media
  104. How Twitter bots affected the US presidential campaign – The Conversation
  105. Advertising is driving social media-fuelled fake news and it is here to stay – The Conversation
  106. 20% of All Election Related Tweets Came From Non-Humans – Futurism
  107. Twitter Bots Dominate 2016 Presidential Election: New Study – Heavy
  108. Tracking The Election With Social Media In Real-Time: How Accurate Is It? – Heavy
  109. BOTS ‘SWAY’ ELECTION Fake tweets by social media robots could swing US Presidential election – The Sun
  110. A fifth of all US election tweets have come from bots – ABC News
  111. The Trump factor tipped to spread to Australian politics as Aussie Truthers push on social media – News .com.au
  112. There are 400,000 Bots That Just Tweet Political Views All Day – Investopedia
  113. Real, or not? USC study finds many political tweets come from fake accounts – Science Blog
  114. Software bots distort Donald Trump support on Twitter: Study – ETCIO
  115. How hackers, social bots, data analysts shaped the U.S. election – The Nation
  116. That swarm of political tweets in your feed? Many could be from bots – The Business Journals
  117. Software ‘bots’ distort Trump support on Twitter – New Vision
  118. Bots Invade Twitter, Spreads Misinformation On US Election – EconoTimes
  119. Software ‘bots’ seen skewing support for Trump on Twitter – The Japan Times
  120. US Presidential Elections 2016: Bot-generated fake tweets influencing US election outcome, says new study – Indian Express
  121. US elections 2016: Researchers show how Twitter bots are trying to influence the poll in favour of Trump – International Business Times
  122. Aliens, and the autopsy into Hillary Clinton’s political death – Toronto SUN
  123. Hillary vs Trump: Most of the election chatter online by Twitter bots, says study – Tech 2 First Post
  124. Twitter bots distort Trump support – iAfrica
  125. Social Media ‘Bots’ Working To Influence U.S. Election – CBS San Francisco
  126. Almost a fifth of election chatter on Twitter comes from bots – Full Act
  127. Software ‘bots’ distort Trump support on Twitter: study – Yahoo! News
  128. Bots Will Break 2016 US Elections Results – iTechPost
  129. Scientist Worries Robot-Generated Tweets Could Compromise The Presidential Election – Newsroom America
  130. Software ‘bots’ distort Trump support on Twitter: study – Phys.org
  131. Spotlight: Fake tweets endanger integrity of U.S. presidential election – XinhuanNet
  132. New Study: Twitter Bots Amount for One-Fifth of US Election Conversation – Dispatch Weekly
  133. Are Robot generated Tweets compromising US Polls? – TechRadar India
  134. Fake tweets endanger integrity of US presidential election – Global Times
  135. Software ‘bots’ distort Trump support on Twitter: study – The Daily Star
  136. Software ‘bots’ distort Trump support on Twitter: study – News Dog
  137. Malicious Twitter bots could have profound consequences for the election – RawStory
  138. ‘Robot-generated fake tweets influencing US election outcome’ – Daily News & Analysis
  139. Sophisticated Bot-Generated Tweets Could Influence Outcome of US Presidential Election – Telegiz
  140. UIC Journal Shows ‘Bots’ Sway Political Discourse, Could Impact Election – NewsWise
  141. Bot-generated tweets could threaten integrity of 2016 US presidential election: Study – BGR
  142. Bot generated tweets influence US Presidential election polls – I4U News
  143. High percentage of robot-generated fake tweets likely to influence public opinion – NewsGram
  144. ‘Robot-generated fake tweets influencing US election outcome’ – Press Trust of India
  145. Robot-generated fake tweets influencing US election outcome: Study – IndianExpress
  146. Fake Tweets, real consequences for the election – Phys.org
  147. Real, or not? USC study finds many political tweets come from fake accounts – USC News
  148. We’re in a digital world filled with lots of social bots – USC News
  149. 23 reasons to get excited about data – IBM Watson Analytics
  150. Algorithm knows when corporate money is pushing memes online – New Scientist
  151. Algorithm identifies artificially promoted Twitter memes and hashtags – The Stack
  152. La fórmula científica que te podría convertir en la próxima Cara Delevingne – Vanitatis
  153. Social Network Sleuths: Investigators Pursue Criminal Gangs Via Phone Chatter – Homeland Security Today
  154. The More You Comment Online, The Dumber Your Comments Become – Huffington Post
  155. The longer you’re on the web, the less interesting your commentary becomes – USC News
  156. Cool study, bro: Why Reddit comments degrade over time – USC Press Room
  157. On Twitter, your positive tweets are actually contagiousThe Daily Dot
  158. Happiness is contagious – USC Viterbi News
  159. Pro-Trump Twitter Bots at Center of Nevada Mystery – Wall Street Journal
  160. How Ebola Infected Twitter: When it comes to sharing online, nothing spreads like fear – Nautilus
  161. Web of lies: Is the internet making a world without truth? – New Scientist
  162. The Top 100 Big Data Experts to Follow in 2016 – Maptive
  163. How DARPA Took On the Twitter Bot Menace with One Hand Behind Its Back – MIT Technology Review
  164. The US government held a contest to identify evil propaganda robots on Facebook and Twitter – Business Insider
  165. Why you need to purge your Twitter feed of angry peopleThe Telegraph
  166. Twitter Emotions Are Contagious, Says New Study, But At Least The Positive Ones Are More So Than The Negative OnesBustle
  167. Twitter users more likely to share happiness than sadness – The Rakyat Post
  168. Twitter reacts positively to upbeat emotions, study findsUSC News
  169. Positive emotions more contagious than negative ones on TwitterPhys.org
  170. On Twitter, Is the Next POTUS a Bot-US?Wall Street Journal
  171. Why Does Facebook Keep Suggesting You Friend Your Tinder Matches?Vice
  172. New data suggest social media brings out the best in us, after allQuartz
  173. Bad news travels fast but positive posts spread wideThe Straits Times
  174. Positive content has greater reachBusiness First Magazine
  175. Data Shows that Positive Content Does Better on Social MediaGood
  176. Why can’t Twitter kill its bots?Fusion
  177. The Algorithm of Instagram FashionThe Science Times
  178. THE SCIENCE OF A SUPERMODELVogue
  179. Here’s how to predict next season’s breakout starsDazed
  180. Instagram Can Determine Which Models Rule the Runway at Fashion WeekStyleCaster
  181. Instagram to predict next ‘It Girl’?HLN Tv
  182. Wondering Who’ll Be This Season’s Breakout Models? Apparently There’s A Mathematical Formula For ThatGrazia Daily
  183. Study Concludes Runway Models With Hips Have a Harder Time Being It Girls – Styleite
  184. FMD Featured in Indiana University Study to Predict Popular Models for NYFWSBWire
  185. NYFW: Instagram May Be Able To Predict Fashion Week’s Top ModelsUniversity Herald
  186. Scientists Can Now Predict How Successful A Model Will BeAskMen
  187. Stylebook snapshot: Researchers study impact of Instagram on models’ successPittsburg Post Gazette
  188. VIDEO: Instagram can predict top models for New York Fashion WeekIrish Examiner
  189. America’s Next Top Model Cycle 22 Winner Predicted By Instagram? Scientists Create Algorithm That Can Do ThatiSchoolGuide
  190. FOLLOWING INSTAGRAM MODELS FOR SCIENCE AND FASHION WEEKNews Ledge
  191. Instagram Correctly Predicts 80% Of Next Top Models At Fashion EventYibada
  192. Instagram can now predict who America’s Next Top Model will beDigital Trends
  193. INSTAGRAM WILL TELL YOU ABOUT TOP MODELS AT THE NEW YORK FASHION WEEKThe Market Business
  194. INSTAGRAM IS QUITE GOOD AT PREDICTING WHO THE NEXT TOP MODEL WILL BERegal Tribune
  195. Instagram can help predict a model’s successRed Orbit
  196. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODELThe Market Business
  197. INSTAGRAM CAN MAKE ACCURATE PREDICTIONS ON SUPERMODELS’ POPULARITYMirror Daily
  198. SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODELWall Street Hedge
  199. NEW ALGORITHM CAN HELP INSTAGRAM PREDICT AMERICA’S NEXT TOP MODELUtah People’s Post
  200. Instagram can predict the NYFW next top model with 80 percent accuracyInferse
  201. Is Instagram the new runway for fashion?Daily O
  202. How Instagram Can Predict Next Supermodels?My Tech Bits
  203. INSTAGRAM WILL TELL YOU WHO IS THE NEXT TOP MODELApex Tribune
  204. Algorithm using Instagram data can predict upcoming top modelNorthern Californian
  205. NYFW: Instagram Could Predict The Next Top ModelUniversity Herald
  206. Instagram Can Now Be Used to Predict the Fashion World’s Next SupermodeliDigitalTimes Australia
    Instagram, Social Media, and New York Fashion WeekPioneer News
  207. Instagram Predicts Future Of Modeling PopularityPress Examiner
  208. Instagram Predicts A Model’s Future Popularity According To Social ScientistsBustle
  209. IU SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODEL USING INSTAGRAMI4U
  210. Instagram Could Be Used To Identify Popularity Level Of Modelsubergizmo
  211. Instagram will tell you industry’s next top modelNature World Report
  212. Next Year’s Fashion Trends: Indiana University Algorithm Employs Instagram Data To Predict The Next Top Models Immortal News
  213. Popularity of models can be gauged using Instagram, study showsTechienews
  214. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODELThe market business
  215. TOP MODELS’ SUCCESS NOW DEPENDS UPON THEIR INSTAGRAM POPULARITYTrinity News Daily
  216. Who will be America’s next top model? Ask InstagramCBS News
  217. This Machine-Learning Algorithm Can Predict the Next Top ModelThe Fashion Spot
  218. New York Fashion Week 2015: Can Scientists Use Instagram To Identify Budding Models?iDigitalTimes
  219. Want To Know If You Can Be A Fashion Model? There’s A Machine-Learning Algorithm For ThatTech Times
  220. SCIENTISTS CAN USE INSTAGRAM TO PREDICT FASHION WEEK’S BIGGEST MODELSHarper’s Bazaar
  221. Scientists Can Now Predict Top Models. Sorry, TyraYahoo! Style
  222. Scientists Figure Out a Formula to Determine Top Model SuccessRacked
  223. Can You Scientifically Predict a Model’s Success?New York Magazine
  224. Machine Learning Algorithm Predicts Which New Faces Will Make It as Fashion ModelsMIT Technology Review
  225. Machine Learning Selects World’s Next Top ModelsCommunications of the ACM
  226. Slack Is Overrun With Bots. Friendly, Wonderful BotsWIRED
  227. The science of SUPERMODELS: Researchers create algorithm that scours Instagram to find the best new talentDaily Mail UK
  228. Machine learning selects world’s next top models it News
  229. IU scientists use Instagram data to forecast top models at New York Fashion WeekIU Bloomington newsroom
  230. This new study suggests sad tweets make you sadFusion
  231. The Power Of Twitter’s Emotional Influence Focus News
  232. Emotions in Tweets Are Contagious: StudyNDTV
  233. Emotions in tweets are contagious Business Standard
  234. Emotions on Twitter are contagious, says studyDNA
  235. ‘Sleeping beauty’ papers slumber for decadesNature News
  236. Even Einstein’s Research Can Take Time to MatterNew York Times
  237. ‘Sleeping beauty’ studies ahead of their timeABC Science
  238. Like Sleeping Beauty, some research lies dormant for decades, study findsPhys.org
  239. The Dayside : Kissed by a princePhysics Today
  240. The Sleeping Beauties of SciencePacific Standard
  241. Quando la ricerca è una “bella addormentata”Le Scienze
  242. Paper all’avanguardia: fanno il botto decenni dopo la pubblicazioneOggi Scienza
  243. ‘Sleeping Beauty’ studies don’t pay off for decadesFuturity
  244. Sleeping Beauty Research Papers Can Languish For Decades, Even For Albert Einstein – Tech Times
  245. Like Sleeping Beauty, Some Research Lies Dormant for Decades News Wise
  246. El estudio de Einstein que resucitó a los 60 años y otras bellas durmientesEl Pais
  247. ‘Sleeping Beauty’ Studies Don’t Pay Off for DecadesEpoch Times
  248. Like Sleeping Beauty, some research lies dormant for decades, IU study finds Indiana University Newsroom
  249. Bot or Not? By James GleickThe New York Review of Books
  250. Twitter’s Bot Problem: Katy Perry, Taylor Swift, Justin Bieber, Rihanna And Other Musicians Have Mostly Fake Followings International Business Times
  251. Why Fear Spreads Faster Than Facts on Social MediaHootsuite
  252. In Social Networking, ‘Weak’ Connections May Be the Most PowerfulVice.com
  253. Fear, Misinformation, and Social Media Complicate Ebola FightTIME
  254. Social media can improve, muddy election campaignsPittsburgh Tribune-Review
  255. How To Spot A Social Bot On TwitterMIT Technology Review
  256. Barack Obama Is Probably a Robot, and Other Lessons from ‘Bot Or Not’Vice.com
  257. Social Bots on Twitter are More Than a Minor NuisanceSocial Times
  258. An Algorithm To Identify Social Bot on Twitter Value Walk
  259. Lying, spamming and scamming on the webThe Spectator
  260. This Algorithm Tells You If A Twitter Account Is a Spam BotMashable
  261. How to Spot A Bot… or Find Out If You Sound Like OneABC News
  262. Lo strumento per distinguere bot e umani su TwitterWired.it
  263. Indiana University Will Devote $1 Million to the Study of Internet MemesThe Mary Sue
  264. The U.S. government is spending $1 million to figure out memesThe Daily Dot
  265. U.S. Military Sends Scouting Party Into the TwitterverseTIME
  266. US military studied how to influence Twitter users in Darpa-funded researchThe Guardian
  267. Twitter Inc Users Studied By US Military In Darpa-Funded ResearchValue Walk
  268. How online ‘chatbots’ are already tricking youBBC
  269. ‘Bot or Not’ App Susses Out Twitter SpambotsTom’s Guide
  270. Computer scientists develop tool for uncovering bot-controlled Twitter accountsPhys.org
  271. IU computer scientists develop tool for uncovering bot-controlled Twitter accountsIU Newsroom
  272. Criminal Gang Connections Mapped via Phone MetadataCommunications of the ACM
  273. New software can map criminal gang connectionsThe Free Press Journal
  274. Gangster science: How police use network theory to track gang membersThe Daily Dot
  275. New software can map criminal gang connectionsBusiness Standard
  276. IU researcher helps Italian police fight crimeThe Washington Times
  277. Criminal gang connections mapped via phone metadataNew Scientist
  278. Mafia Wars: How Italy’s Secret Police Use Metadata To Track Organized CrimeFast Company
  279. LogAnalysis maps the structure of gangs using phone recordsEngadget
  280. How to Detect Criminal Gangs Using Mobile Phone Data MIT Technology Review
  281. Complex networks researcher at IU fighting crime with mobile phone data IU Newsroom
  282. One Tweet if by Land Newsweek
  283. Where do Twitter trends start? Try CincinnatiThe Washington Post
  284. Study: Seattle is top Twitter trendsetter in the U.S.The Seattle Times
  285. The Top Five Trend-Setting Cities on TwitterMIT Technology Review
  286. Study Finds Cincinnati Is Major Twitter Trendsetter in U.S. CityBeat
  287. Seattle generates more nationally-trending topics on Twitter than any other U.S. city, study says GeekWire
  288. Cincinnati is leading the way on TwitterCincyBizBlog
  289. The Anatomy of the Occupy Wall Street Movement on TwitterMIT Technology Review
  290. Data dance, big data and data miningThe Why Files
  291. Cell phone data analysis dials in crime networksScience News
  292. Using statistics to catch cheats and criminalsPhysics Today
  293. Bond with the best: FaceBook vs TwitterTechKnowBits.com
  294. Study: Facebook Builds Better Communities Than TwitterThe Atlantic
  295. Facebook Builds Stronger Bonds Than Twitter, Study SaysMashable
  296. Study shows similarities between Facebook and real-world communitiesLeaders West
  297. Does Facebook Really Create Stronger Bonds Than Twitter?Daily lounge
  298. Facebook Encourages Stronger Bonds Over Twitter: Studyhashtags.org
  299. Facebook and Strongly Connected CommunitiesCornell University
  300. Driven by friendshipSpringerSelect
  301. Facebook is a communityScience Daily
  302. Data-Mining FacebookIdiro Technologies

Press in non-English media

  1. Sui social, i bot hanno influenzato le elezioni statunitensi: Ora si guarda alla Germania – Consumerismo (in Italian)
  2. Bot economy e le leggi di Asimov – Data Manager Online (in Italian)
  3. Difundir noticias falsas es algo común para todos los gobiernos del mundo – Infobae (in Spanish)
  4. El uso de los los bots de Twitter – Panama On (in Spanish)
  5. Los bots aman a Trump y odian a Macron – La Vanguardia (in Spanish)
  6. La incidencia de Fake News en las campañas de Trump y Macron – TyN Magazine (in Spanish)
  7. Twitter bilgi kirliliğini besleyenlerin oyun sahası haline nasıl geliyor?Teyit (in Turkish)
  8. Președintele Trump, prietenul roboților ruși?Cotidianul (in Turkish)
  9. El debate político en Twitter se desinfló a comparación de 2015El Patagonico (in Spanish)
  10. Twitter ist ForschungWELT (in German)
  11. Wie Fake News entstehen und warum sie eine Gefahr darstellen – CT magazine (in German)
  12. El uso de ‘bots’ en las elecciones de Francia, por Donald Trump – Sipse (in Spanish)
  13. Ugyanazok a Twitter robotok kampányoltak Trumpnak és Le Pennek – 444 (in Ukranian)
  14. Pendant la présidentielle, les robots pro-Trump ont joué les anti-Macron sur Twitter – Mashable (in French)
  15. Présidentielle française : les robots pro-Trump ont joué les anti-Macron sur Twitter – France 24 (in French)
  16. Les 18.000 bots qui ont favorisé la diffusion des MacronLeaks – Slate (in French)
  17. Macron Leaks : Les bots pro-Trump utilisés dans la campagne de désinformation – Le Monde (in French)
  18. La falsa realidad creada por los bots en Twitter – The New York Times (in Spanish)
  19. Bad Bot oder Mensch – das ist hier die Frage – Medien Milch (in German)
  20. Studie: Bis zu 48 Millionen Twitter-Nutzer sind in Wirklichkeit Bots – T3N (in German)
  21. Der Aufstieg der Twitter-Bots: 48 Millionen Nutzer sind nicht menschlich – Studie – Sputnik News (in German)
  22. Studie: Bis zu 48 Millionen Nutzer auf Twitter sind Bots – der Standard (in German)
  23. “Blade Runner”-Test für Twitter-Accounts: Bot oder Mensch? – der Standard (in German)
  24. Bot-Paradies Twitter – Sachsische Zeitung (in German)
  25. 15 Prozent Social Bots? – DLF24 (in German)
  26. TWITTER: IST JEDER SIEBTE USER EIN BOT? – UberGizmo (in German)
  27. Twitter: Bis zu 48 Millionen Bot-Profile – Heise (in German)
  28. Studie: Bis zu 15 Prozent aller aktiven, englischsprachigen Twitter-Konten sind Bots – Netzpolitik (in German)
  29. Automatische Erregung – Wiener Zeitung (in German)
  30. 15 por ciento de las cuentas de Twitter son ‘bots’: estudio – CNET (in Spanish)
  31. 48 de los 319 millones de usuarios activos de Twitter son bots – TIC Beat (in Spanish)
  32. 15% de las cuentas de Twitter son ‘bots’ – Merca 2.0 (in Spanish)
  33. 48 de los 319 de usuarios activos en Twitter son bots – MDZ (in Spanish)
  34. Twitter, paradis des «bots»? – Slate (in French)
  35. Twitter compterait 48 millions de comptes gérés par des robots – MeltyStyle (in French)
  36. Twitter : 48 millions de comptes sont des bots – blog du moderateur (in French)
  37. ’30 tot 50 miljoen actieve Twitter-accounts zijn bots’ – NOS (in Dutch)
  38. 48 εκατομμύρια χρήστες στο Twitter δεν είναι άνθρωποι, σύμφωνα με έρευνα Πηγή – LiFo (in Greek)
  39. 48 triệu người dùng Twitter là bot và mối nguy hại – Khoa Hoc Phattrien (in Vietnamese)
  40. Post-vérité – La revue européenne des médias et du numérique (in French)
  41. Twitter, 25 mila account dell’Isis – Pagina99 (in Italian)
  42. Trump su Twitter ha un esercito di bot – Il Post (in Italian)
  43. La violencia extrema del Dáesh en Twitter le ayudó a alzarse frente a Al Qaeda – MIT Technology Review (in Spanish)
  44. Così funziona la propaganda politica a colpi di bot su Twitter – La Stampa (in Italian)
  45. Así explica la ciencia la difusión de noticias falsas en los medios de comunicaciónEl Periodico (in Spanish)
  46. 10 conductas muy contagiosas – Muy Interesante (in Spanish)
  47. Robots behind the millions of tweets: “The integrity at danger” – Svenska Dagbladet (in Swedish)
  48. Elezioni Usa: il 19% dei tweet elettorali è prodotto da software – Repubblica (in Italian)
  49. ¿Cómo nos engañan los ‘bots’ online? – Autobild.es (in Spanish)
  50. El atroz encanto del terror – La Nacion (in Spanish)
  51. La bella addormentata non è una favola di Natale – Giornale dell’università di Padova (in Italian)
  52. Lo que encontramos en las redes sociales afecta cada vez más a nuestro estado de ánimoPuro Marketing (in Spanish)
  53. Tuitea la alegría, que eso se pegaPrimera Hora (in Spanish)
  54. Cómo Facebook y Twitter pueden influir en tu estado de ánimoLa Nacion (in Spanish)
  55. Study: Twitter “infects” people with positive emotionsGazeta.ru (in Russian)
  56. La joie, un sentiment virtuellement plus partagé que la tristesse sur TwitterLe Soir (in French)
  57. La joie, plus partagée que la tristesse sur TwitterLuxemburg Wort (in French)
  58. Modelle e top model, dietro il successo c’è una formula matematicaGrazia (in Italian)
  59. Come cambia la bellezza al tempo di Instagram – La Stampa (in Italian)
  60. Buzz Mode : Instagram ou la clé du succès des mannequins selon une étude de l’université de l’IndianaMelty Fashion (in French)
  61. TOP MODEL, IL SUCCESSO È IN UN ALGORITMOLettera Donna (in Italian)
  62. Un algoritmo italiano prevede il successo delle top modelCorriere (in Italian)
  63. La scienza della “super modella”: arriva l’algoritmo per scovare nuovi talenti sui socialFanpage (in Italian)
  64. Cientistas criam algoritmo que prevê o sucesso das modelos através do InstagramVisão (in Portuguese)
  65. A computer algorithm can predict the popularity of top modelsVesti (Вести.Ru in Russian)
  66. Tomorrow: the United States develop software to predict IG supermodel accuracy rate of 80%Chinatimes (in Chinese)
  67. Likes are more important than the perfect dress size Die Welt (in German)
  68. Twitterbots manipulate political debates and marketsFuturezone (in German)
  69. Il messaggio vola su FacebookFocus (pp. 78 n. 244 – Febbraio 2013) (in Italian)
  70. Come si diffondono le conversazioni? we are social (in Italian)
  71. I confini della socializzazione: non tutto si può condividereMarketingArena (in Italian)