Podcasts & Media

Tech Crunch Podcast: Technotopia 

Faculty Profile: Emilio Ferrara from USC Viterbi on Vimeo.

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

The Rise of Social Bots from CACM on Vimeo.

Press Coverage

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

Press in non-English media

  1. Manipolazioni social nella corsa alla Casa BiancaMicron (in Italian)
  2. I bot di Twitter sono pronti a diffondere disinformazione prima delle elezioniNews H24 (in Italian)
  3. Conspiracoes da web tomam campanha presidencial dos Estados UnidosEstadao (in Portuguese)
  4. La fabbrica dei troll è tornataOggi Scienza (in Italian)
  5. La difficile lotta a bufale e teorie complottiste sul coronavirus – Le Scienze (Scientific American edition in Italian)
  6. Coronavirus : une difficile lutte contre l’épidémie de désinformation – Pour La Science (in French)
  7. Bots en Twitter: Cómo se organizan y operan – La Nacion (in Spanish)
  8. Come smascherare il bot – Le Scienze (Scientific American edition in Italian)
  9. Usar la imperfección humana para detectar botsLa Vanguardia (in Spanish)
  10. Wie man auf Twitter erkennt, dass man mit Robotern streitetDie Press (in German)
  11. Twitterbotar allt större hot mot politiska valResume (in German)
  12. Bots en Twitter incidieron en el 1-O, según un estudio – El Pais (in Spanish)
  13. I robot diventano sempre più invadenti, si fingono umani e diffondono propaganda – Il fatto quotidiano (in Italian)
  14. ‘Bots’ de Twitter van generar “contingut violent” per influir en l’1-O, segons un estudi – El Periodico (in Spanish)
  15. Bots en Twitter promovieron contenido violento en referéndum, según estudio – La Vangardia (in Spanish)
  16. Bots de Twitter van generar contingut violent abans de l’1-O – Regio 7 (in Spanish)
  17. Del mito a la realidad: hasta dónde puede llegar la manipulación electoral de los votantes – infobae (in Spanish)
  18. Los ‘bots’ contaminaron el 1 de octubre con un millón de tuits – El Pais (in Spanish)
  19. Sui social, i bot hanno influenzato le elezioni statunitensi: Ora si guarda alla Germania – Consumerismo (in Italian)
  20. Bot economy e le leggi di Asimov – Data Manager Online (in Italian)
  21. Difundir noticias falsas es algo común para todos los gobiernos del mundo – Infobae (in Spanish)
  22. El uso de los los bots de Twitter – Panama On (in Spanish)
  23. Los bots aman a Trump y odian a Macron – La Vanguardia (in Spanish)
  24. La incidencia de Fake News en las campañas de Trump y Macron – TyN Magazine (in Spanish)
  25. Twitter bilgi kirliliğini besleyenlerin oyun sahası haline nasıl geliyor?Teyit (in Turkish)
  26. Președintele Trump, prietenul roboților ruși?Cotidianul (in Turkish)
  27. El debate político en Twitter se desinfló a comparación de 2015El Patagonico (in Spanish)
  28. Twitter ist ForschungWELT (in German)
  29. Wie Fake News entstehen und warum sie eine Gefahr darstellen – CT magazine (in German)
  30. El uso de ‘bots’ en las elecciones de Francia, por Donald Trump – Sipse (in Spanish)
  31. Ugyanazok a Twitter robotok kampányoltak Trumpnak és Le Pennek – 444 (in Ukranian)
  32. Pendant la présidentielle, les robots pro-Trump ont joué les anti-Macron sur Twitter – Mashable (in French)
  33. Présidentielle française : les robots pro-Trump ont joué les anti-Macron sur Twitter – France 24 (in French)
  34. Les 18.000 bots qui ont favorisé la diffusion des MacronLeaks – Slate (in French)
  35. Macron Leaks : Les bots pro-Trump utilisés dans la campagne de désinformation – Le Monde (in French)
  36. La falsa realidad creada por los bots en Twitter – The New York Times (in Spanish)
  37. Bad Bot oder Mensch – das ist hier die Frage – Medien Milch (in German)
  38. Studie: Bis zu 48 Millionen Twitter-Nutzer sind in Wirklichkeit Bots – T3N (in German)
  39. Der Aufstieg der Twitter-Bots: 48 Millionen Nutzer sind nicht menschlich – Studie – Sputnik News (in German)
  40. Studie: Bis zu 48 Millionen Nutzer auf Twitter sind Bots – der Standard (in German)
  41. “Blade Runner”-Test für Twitter-Accounts: Bot oder Mensch? – der Standard (in German)
  42. Bot-Paradies Twitter – Sachsische Zeitung (in German)
  43. 15 Prozent Social Bots? – DLF24 (in German)
  44. TWITTER: IST JEDER SIEBTE USER EIN BOT? – UberGizmo (in German)
  45. Twitter: Bis zu 48 Millionen Bot-Profile – Heise (in German)
  46. Studie: Bis zu 15 Prozent aller aktiven, englischsprachigen Twitter-Konten sind Bots – Netzpolitik (in German)
  47. Automatische Erregung – Wiener Zeitung (in German)
  48. 15 por ciento de las cuentas de Twitter son ‘bots’: estudio – CNET (in Spanish)
  49. 48 de los 319 millones de usuarios activos de Twitter son bots – TIC Beat (in Spanish)
  50. 15% de las cuentas de Twitter son ‘bots’ – Merca 2.0 (in Spanish)
  51. 48 de los 319 de usuarios activos en Twitter son bots – MDZ (in Spanish)
  52. Twitter, paradis des «bots»? – Slate (in French)
  53. Twitter compterait 48 millions de comptes gérés par des robots – MeltyStyle (in French)
  54. Twitter : 48 millions de comptes sont des bots – blog du moderateur (in French)
  55. ’30 tot 50 miljoen actieve Twitter-accounts zijn bots’ – NOS (in Dutch)
  56. 48 εκατομμύρια χρήστες στο Twitter δεν είναι άνθρωποι, σύμφωνα με έρευνα Πηγή – LiFo (in Greek)
  57. 48 triệu người dùng Twitter là bot và mối nguy hại – Khoa Hoc Phattrien (in Vietnamese)
  58. Post-vérité – La revue européenne des médias et du numérique (in French)
  59. Twitter, 25 mila account dell’Isis – Pagina99 (in Italian)
  60. Trump su Twitter ha un esercito di bot – Il Post (in Italian)
  61. La violencia extrema del Dáesh en Twitter le ayudó a alzarse frente a Al Qaeda – MIT Technology Review (in Spanish)
  62. Così funziona la propaganda politica a colpi di bot su Twitter – La Stampa (in Italian)
  63. Así explica la ciencia la difusión de noticias falsas en los medios de comunicaciónEl Periodico (in Spanish)
  64. 10 conductas muy contagiosas – Muy Interesante (in Spanish)
  65. Robots behind the millions of tweets: “The integrity at danger” – Svenska Dagbladet (in Swedish)
  66. Elezioni Usa: il 19% dei tweet elettorali è prodotto da software – Repubblica (in Italian)
  67. ¿Cómo nos engañan los ‘bots’ online? – Autobild.es (in Spanish)
  68. El atroz encanto del terror – La Nacion (in Spanish)
  69. La bella addormentata non è una favola di Natale – Giornale dell’università di Padova (in Italian)
  70. Lo que encontramos en las redes sociales afecta cada vez más a nuestro estado de ánimoPuro Marketing (in Spanish)
  71. Tuitea la alegría, que eso se pegaPrimera Hora (in Spanish)
  72. Cómo Facebook y Twitter pueden influir en tu estado de ánimoLa Nacion (in Spanish)
  73. Study: Twitter “infects” people with positive emotionsGazeta.ru (in Russian)
  74. La joie, un sentiment virtuellement plus partagé que la tristesse sur TwitterLe Soir (in French)
  75. La joie, plus partagée que la tristesse sur TwitterLuxemburg Wort (in French)
  76. Modelle e top model, dietro il successo c’è una formula matematicaGrazia (in Italian)
  77. Come cambia la bellezza al tempo di Instagram – La Stampa (in Italian)
  78. Buzz Mode : Instagram ou la clé du succès des mannequins selon une étude de l’université de l’IndianaMelty Fashion (in French)
  79. TOP MODEL, IL SUCCESSO È IN UN ALGORITMOLettera Donna (in Italian)
  80. Un algoritmo italiano prevede il successo delle top modelCorriere (in Italian)
  81. La scienza della “super modella”: arriva l’algoritmo per scovare nuovi talenti sui socialFanpage (in Italian)
  82. Cientistas criam algoritmo que prevê o sucesso das modelos através do InstagramVisão (in Portuguese)
  83. A computer algorithm can predict the popularity of top modelsVesti (Вести.Ru in Russian)
  84. Tomorrow: the United States develop software to predict IG supermodel accuracy rate of 80%Chinatimes (in Chinese)
  85. Likes are more important than the perfect dress size Die Welt (in German)
  86. Twitterbots manipulate political debates and marketsFuturezone (in German)
  87. Il messaggio vola su FacebookFocus (pp. 78 n. 244 – Febbraio 2013) (in Italian)
  88. Come si diffondono le conversazioni? we are social (in Italian)
  89. I confini della socializzazione: non tutto si può condividereMarketingArena (in Italian)