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. Social Media Used To Spread Coronavirus Disinformation, And Patient Groups Are Fighting BackNPR
  2. Segregated communities of polarized Twitter users are shaping online conversations about COVID-19PsyPost
  3. Beware of Bots Amid Election Year and Coronavirus PandemicReform Austin
  4. Who’s a Bot? Who’s Not?The New York Times
  5. The epic battle against coronavirus misinformation and conspiracy theoriesNature
  6. AI can distinguish between bots and humans based on Twitter activityNew Scientist
  7. Laziness is sure sign it’s not a botThe Times
  8. Bot or Not? AI looks at Twitter behavior to sort real accounts from fakeDigital Trends
  9. Laziness is the key human trait that tells us apart from artificially intelligent ‘bots’ on social mediaDaily Mail
  10. Study reveals behavioral differences between bots and humans that could inform new machine learning algorithmsTechXplore
  11. Researchers develop AI-based system to detect Twitter botsGadgets Now
  12. Bot or not? A.I. looks at Twitter behavior to sort real accounts from fakeBrinkwire
  13. AI Can Distinguish Between Bots, Humans Based on Twitter ActivityCommunications of the ACM
  14. What are the characteristics of human beings who have not been able to reproduce social media bots that continue to evolve like humans?Gigazine
  15. AI study of Twitter bots reveals boredom is what separates us from machinesTNW
  16. What’s human and what’s not when we talk?COSMOS
  17. Researchers train AI to spot difference between bots and human users on Twitter based on their activity patternsComputing
  18. Tiredness could be ‘human signature’ used to detect bots on TwitterE&T
  19. AI can spot a bear bot at 20 pacesFudzilla
  20. Online Behavioral Signatures Aid Development of Bot Detection SoftwareCourthouse News Service
  21. Bot detector may now be able to see clear ‘human signature’ in tweetsSiliconRepublic
  22. Researchers train AI to detect Twitter botsIndian Express Indulge
  23. Laziness is very important: it’s what makes us human, and what may help us stop online spamIndia Times
  24. This AI can now detect Twitter bots: See how it worksIndia TV
  25. USC Researchers Release Public Coronavirus Twitter Set for AcademicsUSC
  26. How malicious Twitter bots evolve to evade detectionThe Irish Times
  27. Twitter ‘Bots’ Becoming More ‘Human,’ Will Influence 2020 Presidential Election, New Research Study SaysInquisitr
  28. As 2020 Election Nears, Twitter Bots Have Only Gotten Better at Seeming HumanAdWeek
  29. Social media bots becoming more human and difficult to detect, study showsE&T
  30. Twitter Bots Are Becoming More Human-LikeDefenseOne
  31. Bots evolving to better mimic humans during electionsHelpNet Security
  32. Modern Politics: Social Media Bots Will Be Harder To Detect During 2020 ElectionStudyFinds
  33. Fake Accounts On Social Media Now Able To Copy Human BehaviourNewsGram
  34. Bots harder to discern from humans have multiplied in online ‘arms race’ – SiliconRepublic
  35. Get ready for more humanlike bots, better deep-fake videos and wall-to-wall disinformation in 2020 race – The Baltimore Sun
  36. Bots might prove harder to detect in 2020 elections – EurekAlert!
  37. Bots in the TwitterspherePEW Research Center
  38. Social Media Bots Deceive E-cigarette Users – Scientific American
  39. Twitter bots were more active than previously known during the 2018 midterms – CNBC
  40. Majority of Twitter bots affecting US elections originated from Russia and Iran – Devdiscourse
  41. About 20% of election posts on Twitter last fall were ‘bots,’ study says – Breitbart
  42. Thousands of Twitter bots active during 2018 US mid-term elections – The Economic Times
  43. How Twitter bots get people to spread fake news – ScienceNews
  44. Study: It only takes a few seconds for bots to spread misinformation – ArsTecnica
  45. Bots actually target and pursue individual influencers – EurekAlert!
  46. The charge of the chatbots: how do you tell who’s human online? – The Guardian
  47. Facebook’s Secret Weapon for Fighting Election Interference: The Government – Bloomberg
  48. Surge in anonymous Asia Twitter accounts sparks bot fears – The Japan Times
  49. The endless game of cat and mouse with spammers – Eureka
  50. Fake news is about to get a lot worse. That will make it easier to violate human rightsThe Washington Post
  51. The Big, Bad Bot Problem – The Ringer
  52. Twitter Cracks Down on Bot Abuse – How Stuff Works
  53. Conservatives amplified Russian trolls 30 times more often than liberals in 2016 – Vox
  54. US conservatives spread tweets by Russian trolls over 30 times more often than liberals – MIT Tech Review
  55. How to Stop Russia From Wrecking Election 2018 – Daily Beast
  56. Twitter has been ignoring its fake account problem for yearsColumbia Journalism Review
  57. Twitter’s huge bot problem is out of the bagCNET
  58. Putin’s Pro-Trump Trolls Just Targeted Hillary Clinton and Robert Mueller – Mother Jones
  59. Twitter urged firms to delete data during 2016 campaign – POLITICO
  60. Bot-hunting Twitter bot sniffs out bogus political tweets – TechCrunch
  61. This new Twitter account hunts for bots that push political opinions – Quartz
  62. Lies, statistics and Twitter – Millennium Post
  63. Social media bots are a real problem and California may regulate them – Medianama
  64. Watch: Five Ways the Internet Is Destroying Society – IEEE Electronics 360
  65. Ending fake news means changing how Wall Street values Facebook and Twitter – Quartz
  66. Trolls, bots and fake news: the mysterious world of social media manipulation – Newsweek
  67. Twitter Bots Distorted the 2016 Election—Including Many Likely From Russia – Mother Jones
  68. Researcher Emilio Ferrara talks about the rise of fake news and botnets – Tech Crunch
  69. These Scientists Wanted To Understand Twitter’s Bot Armies, So They Built Their Own – Fast Company
  70. Senator Slams Twitter’s Disclosure On Russian Meddling As ‘Inadequate On Every Level’ – Forbes
  71. Twitter’s Disclosure of Russian Activity Sparks Criticism From Lawmakers – The Wall Street Journal
  72. Twitter takes its turn in the Russian probe spotlight – Politico
  73. Twitter Says It Found 201 Russia-Linked Accounts That Aimed to Influence U.S. Election – Fox Business
  74. TWITTER STORMS – Civicist
  75. JACK DORSEY TAKES HIS TURN IN THE RUSSIA PROBE BARREL – Vanity Fair
  76. Fake News on Twitter Flooded Swing States That Helped Trump Win – Mother Jones
  77. Twitter to Testify Before Senate in Russia Probe – US News
  78. Researchers find that Twitter bots can be used for good – Tech Crunch
  79. Twitter Bots Can Encourage Decent Conduct, Not Just Fake News – News18
  80. Twitter bots for good: USC ISI study reveals how information spreads on social media – EurekAlert!
  81. Germany Election So Far Unaffected by ‘Fake News’ – Snopes
  82. Social media ‘bots’ tried to influence the U.S. election. Germany may be nextScience
  83. Computational propaganda poses challengeGlobal Times
  84. Russia’s propaganda machine amplifies alt-right – The Hill
  85. #FireMcMaster, Not Damore: Twitter Bots Are Thriving, And They’re More Lethal Than Ever – Fast Company
  86. Why didn’t Macron leaks carry more clout in the French presidential election? USC News
  87. The curious case of ‘Nicole Mincey,’ the Trump fan who may actually be a botThe Washington Post
  88. Trump Thanked A ‘Supporter’ On Twitter, Then A Mystery UnraveledA Plus
  89. Spreading fake news becomes standard practice for governments across the world – The Washington Post
  90. One in five bots sharing fake news during France’s presidential election were also involved in the United States’ – ZME Science
  91. Black-market bots, duped humans are responsible for derailing elections with fake news – ThinkProgress
  92. Study: Bots have turned Twitter into a powerful political disinformation platform – Venture Beat
  93. Fake news bots are so economical, you can use them over and over – Harvard NiemanLab
  94. Pro-Trump Twitter bots were also used to target Macron, research shows – The Verge
  95. There’s a Bit of Overlap Between Bots Trying to Manipulate American and French Elections – New York Magazine
  96. Research links pro-Trump, anti-Macron Twitter bots – The Hill
  97. The Same Twitter Bots That Helped Trump Tried to Sink Macron, Researcher Says – VICE
  98. How the Hashtag Is Changing Warfare – SIGNAL
  99. How Twitter Is Being Gamed to Feed Misinformation – New York Times
  100. ‘Something fishy’ is going on with Trump’s twitter account, researchers say – Washington Post
  101. Inside Russia’s Social Media War on America – TIME (cover story)
  102. The Twitter Bots Who Tried to Steal France – Daily Beast
  103. When Facebook and Instagram Think You’re Depressed – VICE
  104. Twitter Has a Serious Problem—And It’s Actually a Bigger Deal Than People Realize – Mother Jones
  105. Sleeping Beauties of Science – Scientific American
  106. Twitter Bot — or Not? – The New York Times
  107. After political Twitter bot revelation, are companies at risk? – Computer World
  108. Searching for proof of Amy – San Francisco Examiner
  109. News That 48 Million Of Twitter’s Users May Be Bots Could Impact Its Valuation – Forbes
  110. How to save Twitter, two pennies at a time – The Denver Post
  111. How Understanding Identity Can Help Avoid Fraudulent Traffic – DMNews
  112. Fake accounts scandal weighs on Twitter boss – The Times
  113. Pressure Grows on Twitter CEO Dorsey Amid Bot Scandal – The Street
  114. CMO Today: Marketers and Political Wonks Gather for SXSW – The Wall Street Journal
  115. Huge number of Twitter accounts are not operated by humans – ABC News
  116. Early Twitter investor Chris Sacca says he ‘hates’ the stock, calls bot issue ‘embarrassing’ – CNBC
  117. Up to 48 million Twitter accounts are bots, study says – CNET
  118. R u bot or not? – VICE
  119. New Machine Learning Framework Uncovers Twitter’s Vast Bot Population – VICE/Motherboard
  120. A Whopping 48 Million Twitter Accounts Are Actually Just Bots, Study Says – Tech Times
  121. 15 Percent Of Twitter Accounts May Be Bots [STUDY] – Value Walk
  122. Why the Rise of Bots is a Concern for Social Networks – Enterpreneuer
  123. Study reveals whopping 48M Twitter accounts are actually bots – CBS News
  124. Twitter is home to nearly 48 million bots, according to report – The Daily Dot
  125. As many as 48 million Twitter accounts aren’t people, says study – CNBC
  126. New Study Says 48 Million Accounts On Twitter Are Bots – We are social media
  127. Almost 48 million Twitter accounts are bots – Axios
  128. Twitter user accounts: around 15% or 48 million are bots [study] – The Vanguard
  129. Report: 48 Million Twitter Accounts Are Bots – Breitbart
  130. Rise of the TWITTERBOTS – Daily Mail
  131. 15 per cent of Twitter is bots, but not the Kardashian kind – The Inquirer
  132. 48 mn Twitter accounts are bots, says study – The Economic Times
  133. 9-15 per cent of Twitter accounts are bots, reveals study – Financial Express
  134. Nearly 48 million Twitter accounts are bots: study – Deccan herald
  135. Study: Nearly 48 Million Twitter Accounts Are Fake; Many Push Political Agendas – The Libertarian Republic
  136. As many as 48 million accounts on Twitter are actually bots, study finds – Sacramento Bee
  137. Study Reveals Roughly 48M Twitter Accounts Are Actually Bots – CBS DFW
  138. Up to 48 million Twitter accounts may be Bots – Financial Buzz
  139. Up to 15% of Twitter accounts are not real people – Blasting News
  140. Tech Bytes: Twitter is Being Invaded by Bots – WDIO Eyewitness News
  141. About 9-15% of Twitter accounts are bots: Study – The Indian Express
  142. Twitter Has Nearly 48 Million Bot Accounts, So Don’t Get Hurt By All Those Online Trolls – India Times
  143. Twitter May Have 45 Million Bots on Its Hands – Investopedia
  144. Bots run amok on Twitter – My Broadband
  145. 9-15% of Twitter accounts are bots: Study – MENA FN
  146. Up To 15 Percent Of Twitter Users Are Bots, Study Says – Vocativ
  147. 48 million active Twitter accounts could be bots – Gearbrain
  148. Study: 15% of Twitter accounts could be bots – Marketing Dive
  149. 15% of Twitter users are actually bots, study claims – MemeBurn
  150. Almost 48 million Twitter accounts are bots – Click Lancashire
  151. As many as 48 million or around 15% of Twitter accounts are bots – TechWorm
  152. Twitter Has an Overwhelming 48 Million Bot Accounts – GineersNow
  153. Data Mining Reveals the Rise of ISIS Propaganda on Twitter – MIT Technology Review
  154. Data Mining Technology Helped Analyze ISIS Rise to Power – iHLS
  155. As a conservative Twitter user sleeps, his account is hard at work – Washington Post
  156. How a Chicago man posts hundreds of pro-Trump tweets each day – Daily Herald
  157. You’ve probably been tricked by fake news and don’t know it – Science News
  158. Twitter Bots Favored Trump Leading Up to Election – U.S. News
  159. How the Bot-y Politic Influenced This Election – MIT Technology Review
  160. Facebook, Twitter & Trump – The New York Review of Books
  161. How Twitter bots played a role in electing Donald Trump – WIRED
  162. Twitter Bots Pollute Public’s Understanding of Politics – Newsweek
  163. How Twitter bots helped Donald Trump win the US presidential election – Arstechnica
  164. On Twitter, No One Knows You Are a Trump Bot – Fast Company
  165. The Algorithmic Democracy – Fast Co. Design
  166. Election 2016 Belongs to the Twitter Bots – VICE
  167. USC Study Finds Many Political Tweets Come From Fake Accounts – CACM News
  168. Almost a fifth of election chatter on Twitter comes from bots – Fusion
  169. Study reports that nearly 20% of election-related tweets were ‘algorithmically driven’ – Talking New Media
  170. How Twitter bots affected the US presidential campaign – The Conversation
  171. Advertising is driving social media-fuelled fake news and it is here to stay – The Conversation
  172. 20% of All Election Related Tweets Came From Non-Humans – Futurism
  173. Twitter Bots Dominate 2016 Presidential Election: New Study – Heavy
  174. Tracking The Election With Social Media In Real-Time: How Accurate Is It? – Heavy
  175. BOTS ‘SWAY’ ELECTION Fake tweets by social media robots could swing US Presidential election – The Sun
  176. A fifth of all US election tweets have come from bots – ABC News
  177. The Trump factor tipped to spread to Australian politics as Aussie Truthers push on social media – News .com.au
  178. There are 400,000 Bots That Just Tweet Political Views All Day – Investopedia
  179. Real, or not? USC study finds many political tweets come from fake accounts – Science Blog
  180. Software bots distort Donald Trump support on Twitter: Study – ETCIO
  181. How hackers, social bots, data analysts shaped the U.S. election – The Nation
  182. That swarm of political tweets in your feed? Many could be from bots – The Business Journals
  183. Software ‘bots’ distort Trump support on Twitter – New Vision
  184. Bots Invade Twitter, Spreads Misinformation On US Election – EconoTimes
  185. Software ‘bots’ seen skewing support for Trump on Twitter – The Japan Times
  186. US Presidential Elections 2016: Bot-generated fake tweets influencing US election outcome, says new study – Indian Express
  187. US elections 2016: Researchers show how Twitter bots are trying to influence the poll in favour of Trump – International Business Times
  188. Aliens, and the autopsy into Hillary Clinton’s political death – Toronto SUN
  189. Hillary vs Trump: Most of the election chatter online by Twitter bots, says study – Tech 2 First Post
  190. Twitter bots distort Trump support – iAfrica
  191. Social Media ‘Bots’ Working To Influence U.S. Election – CBS San Francisco
  192. Almost a fifth of election chatter on Twitter comes from bots – Full Act
  193. Software ‘bots’ distort Trump support on Twitter: study – Yahoo! News
  194. Bots Will Break 2016 US Elections Results – iTechPost
  195. Scientist Worries Robot-Generated Tweets Could Compromise The Presidential Election – Newsroom America
  196. Software ‘bots’ distort Trump support on Twitter: study – Phys.org
  197. Spotlight: Fake tweets endanger integrity of U.S. presidential election – XinhuanNet
  198. New Study: Twitter Bots Amount for One-Fifth of US Election Conversation – Dispatch Weekly
  199. Are Robot generated Tweets compromising US Polls? – TechRadar India
  200. Fake tweets endanger integrity of US presidential election – Global Times
  201. Software ‘bots’ distort Trump support on Twitter: study – The Daily Star
  202. Software ‘bots’ distort Trump support on Twitter: study – News Dog
  203. Malicious Twitter bots could have profound consequences for the election – RawStory
  204. ‘Robot-generated fake tweets influencing US election outcome’ – Daily News & Analysis
  205. Sophisticated Bot-Generated Tweets Could Influence Outcome of US Presidential Election – Telegiz
  206. UIC Journal Shows ‘Bots’ Sway Political Discourse, Could Impact Election – NewsWise
  207. Bot-generated tweets could threaten integrity of 2016 US presidential election: Study – BGR
  208. Bot generated tweets influence US Presidential election polls – I4U News
  209. High percentage of robot-generated fake tweets likely to influence public opinion – NewsGram
  210. ‘Robot-generated fake tweets influencing US election outcome’ – Press Trust of India
  211. Robot-generated fake tweets influencing US election outcome: Study – IndianExpress
  212. Fake Tweets, real consequences for the election – Phys.org
  213. Real, or not? USC study finds many political tweets come from fake accounts – USC News
  214. We’re in a digital world filled with lots of social bots – USC News
  215. 23 reasons to get excited about data – IBM Watson Analytics
  216. Algorithm knows when corporate money is pushing memes online – New Scientist
  217. Algorithm identifies artificially promoted Twitter memes and hashtags – The Stack
  218. La fórmula científica que te podría convertir en la próxima Cara Delevingne – Vanitatis
  219. Social Network Sleuths: Investigators Pursue Criminal Gangs Via Phone Chatter – Homeland Security Today
  220. The More You Comment Online, The Dumber Your Comments Become – Huffington Post
  221. The longer you’re on the web, the less interesting your commentary becomes – USC News
  222. Cool study, bro: Why Reddit comments degrade over time – USC Press Room
  223. On Twitter, your positive tweets are actually contagiousThe Daily Dot
  224. Happiness is contagious – USC Viterbi News
  225. Pro-Trump Twitter Bots at Center of Nevada Mystery – Wall Street Journal
  226. How Ebola Infected Twitter: When it comes to sharing online, nothing spreads like fear – Nautilus
  227. Web of lies: Is the internet making a world without truth? – New Scientist
  228. The Top 100 Big Data Experts to Follow in 2016 – Maptive
  229. How DARPA Took On the Twitter Bot Menace with One Hand Behind Its Back – MIT Technology Review
  230. The US government held a contest to identify evil propaganda robots on Facebook and Twitter – Business Insider
  231. Why you need to purge your Twitter feed of angry peopleThe Telegraph
  232. Twitter Emotions Are Contagious, Says New Study, But At Least The Positive Ones Are More So Than The Negative OnesBustle
  233. Twitter users more likely to share happiness than sadness – The Rakyat Post
  234. Twitter reacts positively to upbeat emotions, study findsUSC News
  235. Positive emotions more contagious than negative ones on TwitterPhys.org
  236. On Twitter, Is the Next POTUS a Bot-US?Wall Street Journal
  237. Why Does Facebook Keep Suggesting You Friend Your Tinder Matches?Vice
  238. New data suggest social media brings out the best in us, after allQuartz
  239. Bad news travels fast but positive posts spread wideThe Straits Times
  240. Positive content has greater reachBusiness First Magazine
  241. Data Shows that Positive Content Does Better on Social MediaGood
  242. Why can’t Twitter kill its bots?Fusion
  243. The Algorithm of Instagram FashionThe Science Times
  244. THE SCIENCE OF A SUPERMODELVogue
  245. Here’s how to predict next season’s breakout starsDazed
  246. Instagram Can Determine Which Models Rule the Runway at Fashion WeekStyleCaster
  247. Instagram to predict next ‘It Girl’?HLN Tv
  248. Wondering Who’ll Be This Season’s Breakout Models? Apparently There’s A Mathematical Formula For ThatGrazia Daily
  249. Study Concludes Runway Models With Hips Have a Harder Time Being It Girls – Styleite
  250. FMD Featured in Indiana University Study to Predict Popular Models for NYFWSBWire
  251. NYFW: Instagram May Be Able To Predict Fashion Week’s Top ModelsUniversity Herald
  252. Scientists Can Now Predict How Successful A Model Will BeAskMen
  253. Stylebook snapshot: Researchers study impact of Instagram on models’ successPittsburg Post Gazette
  254. VIDEO: Instagram can predict top models for New York Fashion WeekIrish Examiner
  255. America’s Next Top Model Cycle 22 Winner Predicted By Instagram? Scientists Create Algorithm That Can Do ThatiSchoolGuide
  256. FOLLOWING INSTAGRAM MODELS FOR SCIENCE AND FASHION WEEKNews Ledge
  257. Instagram Correctly Predicts 80% Of Next Top Models At Fashion EventYibada
  258. Instagram can now predict who America’s Next Top Model will beDigital Trends
  259. INSTAGRAM WILL TELL YOU ABOUT TOP MODELS AT THE NEW YORK FASHION WEEKThe Market Business
  260. INSTAGRAM IS QUITE GOOD AT PREDICTING WHO THE NEXT TOP MODEL WILL BERegal Tribune
  261. Instagram can help predict a model’s successRed Orbit
  262. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODELThe Market Business
  263. INSTAGRAM CAN MAKE ACCURATE PREDICTIONS ON SUPERMODELS’ POPULARITYMirror Daily
  264. SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODELWall Street Hedge
  265. NEW ALGORITHM CAN HELP INSTAGRAM PREDICT AMERICA’S NEXT TOP MODELUtah People’s Post
  266. Instagram can predict the NYFW next top model with 80 percent accuracyInferse
  267. Is Instagram the new runway for fashion?Daily O
  268. How Instagram Can Predict Next Supermodels?My Tech Bits
  269. INSTAGRAM WILL TELL YOU WHO IS THE NEXT TOP MODELApex Tribune
  270. Algorithm using Instagram data can predict upcoming top modelNorthern Californian
  271. NYFW: Instagram Could Predict The Next Top ModelUniversity Herald
  272. Instagram Can Now Be Used to Predict the Fashion World’s Next SupermodeliDigitalTimes Australia
    Instagram, Social Media, and New York Fashion WeekPioneer News
  273. Instagram Predicts Future Of Modeling PopularityPress Examiner
  274. Instagram Predicts A Model’s Future Popularity According To Social ScientistsBustle
  275. IU SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODEL USING INSTAGRAMI4U
  276. Instagram Could Be Used To Identify Popularity Level Of Modelsubergizmo
  277. Instagram will tell you industry’s next top modelNature World Report
  278. Next Year’s Fashion Trends: Indiana University Algorithm Employs Instagram Data To Predict The Next Top Models Immortal News
  279. Popularity of models can be gauged using Instagram, study showsTechienews
  280. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODELThe market business
  281. TOP MODELS’ SUCCESS NOW DEPENDS UPON THEIR INSTAGRAM POPULARITYTrinity News Daily
  282. Who will be America’s next top model? Ask InstagramCBS News
  283. This Machine-Learning Algorithm Can Predict the Next Top ModelThe Fashion Spot
  284. New York Fashion Week 2015: Can Scientists Use Instagram To Identify Budding Models?iDigitalTimes
  285. Want To Know If You Can Be A Fashion Model? There’s A Machine-Learning Algorithm For ThatTech Times
  286. SCIENTISTS CAN USE INSTAGRAM TO PREDICT FASHION WEEK’S BIGGEST MODELSHarper’s Bazaar
  287. Scientists Can Now Predict Top Models. Sorry, TyraYahoo! Style
  288. Scientists Figure Out a Formula to Determine Top Model SuccessRacked
  289. Can You Scientifically Predict a Model’s Success?New York Magazine
  290. Machine Learning Algorithm Predicts Which New Faces Will Make It as Fashion ModelsMIT Technology Review
  291. Machine Learning Selects World’s Next Top ModelsCommunications of the ACM
  292. Slack Is Overrun With Bots. Friendly, Wonderful BotsWIRED
  293. The science of SUPERMODELS: Researchers create algorithm that scours Instagram to find the best new talentDaily Mail UK
  294. Machine learning selects world’s next top models it News
  295. IU scientists use Instagram data to forecast top models at New York Fashion WeekIU Bloomington newsroom
  296. This new study suggests sad tweets make you sadFusion
  297. The Power Of Twitter’s Emotional Influence Focus News
  298. Emotions in Tweets Are Contagious: StudyNDTV
  299. Emotions in tweets are contagious Business Standard
  300. Emotions on Twitter are contagious, says studyDNA
  301. ‘Sleeping beauty’ papers slumber for decadesNature News
  302. Even Einstein’s Research Can Take Time to MatterNew York Times
  303. ‘Sleeping beauty’ studies ahead of their timeABC Science
  304. Like Sleeping Beauty, some research lies dormant for decades, study findsPhys.org
  305. The Dayside : Kissed by a princePhysics Today
  306. The Sleeping Beauties of SciencePacific Standard
  307. Quando la ricerca è una “bella addormentata”Le Scienze
  308. Paper all’avanguardia: fanno il botto decenni dopo la pubblicazioneOggi Scienza
  309. ‘Sleeping Beauty’ studies don’t pay off for decadesFuturity
  310. Sleeping Beauty Research Papers Can Languish For Decades, Even For Albert Einstein – Tech Times
  311. Like Sleeping Beauty, Some Research Lies Dormant for Decades News Wise
  312. El estudio de Einstein que resucitó a los 60 años y otras bellas durmientesEl Pais
  313. ‘Sleeping Beauty’ Studies Don’t Pay Off for DecadesEpoch Times
  314. Like Sleeping Beauty, some research lies dormant for decades, IU study finds Indiana University Newsroom
  315. Bot or Not? By James GleickThe New York Review of Books
  316. Twitter’s Bot Problem: Katy Perry, Taylor Swift, Justin Bieber, Rihanna And Other Musicians Have Mostly Fake Followings International Business Times
  317. Why Fear Spreads Faster Than Facts on Social MediaHootsuite
  318. In Social Networking, ‘Weak’ Connections May Be the Most PowerfulVice.com
  319. Fear, Misinformation, and Social Media Complicate Ebola FightTIME
  320. Social media can improve, muddy election campaignsPittsburgh Tribune-Review
  321. How To Spot A Social Bot On TwitterMIT Technology Review
  322. Barack Obama Is Probably a Robot, and Other Lessons from ‘Bot Or Not’Vice.com
  323. Social Bots on Twitter are More Than a Minor NuisanceSocial Times
  324. An Algorithm To Identify Social Bot on Twitter Value Walk
  325. Lying, spamming and scamming on the webThe Spectator
  326. This Algorithm Tells You If A Twitter Account Is a Spam BotMashable
  327. How to Spot A Bot… or Find Out If You Sound Like OneABC News
  328. Lo strumento per distinguere bot e umani su TwitterWired.it
  329. Indiana University Will Devote $1 Million to the Study of Internet MemesThe Mary Sue
  330. The U.S. government is spending $1 million to figure out memesThe Daily Dot
  331. U.S. Military Sends Scouting Party Into the TwitterverseTIME
  332. US military studied how to influence Twitter users in Darpa-funded researchThe Guardian
  333. Twitter Inc Users Studied By US Military In Darpa-Funded ResearchValue Walk
  334. How online ‘chatbots’ are already tricking youBBC
  335. ‘Bot or Not’ App Susses Out Twitter SpambotsTom’s Guide
  336. Computer scientists develop tool for uncovering bot-controlled Twitter accountsPhys.org
  337. IU computer scientists develop tool for uncovering bot-controlled Twitter accountsIU Newsroom
  338. Criminal Gang Connections Mapped via Phone MetadataCommunications of the ACM
  339. New software can map criminal gang connectionsThe Free Press Journal
  340. Gangster science: How police use network theory to track gang membersThe Daily Dot
  341. New software can map criminal gang connectionsBusiness Standard
  342. IU researcher helps Italian police fight crimeThe Washington Times
  343. Criminal gang connections mapped via phone metadataNew Scientist
  344. Mafia Wars: How Italy’s Secret Police Use Metadata To Track Organized CrimeFast Company
  345. LogAnalysis maps the structure of gangs using phone recordsEngadget
  346. How to Detect Criminal Gangs Using Mobile Phone Data MIT Technology Review
  347. Complex networks researcher at IU fighting crime with mobile phone data IU Newsroom
  348. One Tweet if by Land Newsweek
  349. Where do Twitter trends start? Try CincinnatiThe Washington Post
  350. Study: Seattle is top Twitter trendsetter in the U.S.The Seattle Times
  351. The Top Five Trend-Setting Cities on TwitterMIT Technology Review
  352. Study Finds Cincinnati Is Major Twitter Trendsetter in U.S. CityBeat
  353. Seattle generates more nationally-trending topics on Twitter than any other U.S. city, study says GeekWire
  354. Cincinnati is leading the way on TwitterCincyBizBlog
  355. The Anatomy of the Occupy Wall Street Movement on TwitterMIT Technology Review
  356. Data dance, big data and data miningThe Why Files
  357. Cell phone data analysis dials in crime networksScience News
  358. Using statistics to catch cheats and criminalsPhysics Today
  359. Bond with the best: FaceBook vs TwitterTechKnowBits.com
  360. Study: Facebook Builds Better Communities Than TwitterThe Atlantic
  361. Facebook Builds Stronger Bonds Than Twitter, Study SaysMashable
  362. Study shows similarities between Facebook and real-world communitiesLeaders West
  363. Does Facebook Really Create Stronger Bonds Than Twitter?Daily lounge
  364. Facebook Encourages Stronger Bonds Over Twitter: Studyhashtags.org
  365. Facebook and Strongly Connected CommunitiesCornell University
  366. Driven by friendshipSpringerSelect
  367. Facebook is a communityScience Daily
  368. Data-Mining FacebookIdiro Technologies

Press in non-English media

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