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

Press in non-English media

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