HUMANS LAB
HomeResearchPeoplePublicationsDatasetsResourcesTeachingMediaBlog

In the news

Media Coverage

Podcasts & Media

January 17, 2025 – Morning Session Research Presentations

Linde Center for Science, Society & Policy · 2026

Introducing Dr. Emilio Ferrara as a Distinguished Speaker on the AI Panel, CIF 2024

Helen Fu Thomas · 2024

Characterizing social media manipulation in the 2020 US presidential election

Emilio Ferrara · 2024

USC Viterbi Webinar on digital technologies for COVID-19

USC Viterbi · 2020

The History of Digital Spam

USC Viterbi · 2019

Machine Learning for Bot Analysis

Unhacking Democracy, ep. 05 · 2018

Technotopia: the rise of fake news and botnets

TechCrunch podcast · 2017

Twitter Bots & the Presidential Campaign

USC Viterbi · 2016

Faculty Profile: Emilio Ferrara

USC Viterbi · 2016

Spotlight: How Emotions Spread on Twitter

USC Viterbi · 2016

The Rise of Social Bots

CACM · 2016

Press Coverage

  1. USC Breakthrough Could Help Scientists Spot Disease Clusters, Fraud Networks and More – USC News
  2. What If We Could See Disinformation Coming? USC Scientists Say We Can – USC ISI News
  3. In simulation, AI agents coordinated propaganda campaign with no further human input – The Washington Times
  4. Misinformation, Bots, and Algorithms: Dr. Emilio Ferrara on Technology’s Impact on Democracy – XRDS: The ACM Magazine for Students
  5. No humans allowed: scientific AI agents get their own social network – Nature
  6. Is fashion ready for the rise of AI stylists? – DAZED
  7. Bot Networks Are Helping Drag Consumer Brands Into the Culture Wars – Wall Street Journal
  8. Many divisive X accounts are foreign-based. What does that tell us?– The Christian Science Monitor
  9. Trump posted a fake Taylor Swift image. AI and deepfakes are only going to get worse this election cycle – LA Times
  10. AI could transform health care, but will it live up to the hype? – Science News
  11. Rapid spread of election disinformation stokes alarm – The Hill
  12. USC researchers offer a glimpse inside the right-wing echo chamber on X and Telegram – FastCo
  13. Researchers uncover an information operation threatening the 2024 U.S. Presidential Election – USC News
  14. How AI deepfakes test voter confidence and election integrity – The Christian Science Monitor
  15. What Are The Risks of Living in a GenAI Synthetic Reality? – Election Integrity Initiative
  16. Charting the Landscape of Nefarious Uses of Generative Artificial Intelligence for Online Election Interference– Election Integrity Initiative
  17. Online ‘likes’ for toxic social media posts prompt more − and more hateful − messages – The Conversation
  18. Social media trolls are inspired by ‘likes’ — not hate: study – New York Post
  19. Eliminating bias in AI may be impossible – a computer scientist explains how to tame it instead – The Conversation
  20. As Twitter’s new owner, Musk gets his chance to defeat bots – CBS News
  21. Musk now gets chance to defeat Twitter’s many fake accounts – The Associated Press (republished in over a hundred other news sites)
  22. Musk wars with Twitter over his buyout deal  on Twitter – Daily Herald
  23. Twitter May Be Poised to Become a Hellscape Just in Time for the Midterms – Slate
  24. Will AI turn the tide in midterm elections? – The American Bazaar
  25. Elon Musk announces content moderation council for Twitter – Mint
  26. Fusing communications with computer science to track down social media manipulators – USC News
  27. Why the polls were so far off in the 2020 election – Fast Company
  28. Spotting political indicators without the polls – Axios
  29. Study Considers a Link Between QAnon and Polling Errors – The New York Times
  30. Were voters manipulated by QAnon a force behind Trump’s ‘red wave’ in 2020 election? – USA TODAY
  31. Russian Disinformation: All Bot But No Bite? – NextGov
  32. Good Bots, Bad Bots, and What You Can Do About Both – F5 Labs
  33. Elon Musk wars with Twitter over his buyout deal – on Twitter – AP News
  34. Musk puts Twitter buy ‘on hold,’ casting doubt on $44B deal – AP News
  35. The systemic factors wedging a persistent gender gap in science – COSMOS
  36. Researchers find fake news about controversial topics contributes to political polarization – Phys.org
  37. Elon Musk says his deal to buy Twitter is on hold – CNN
  38. The next-generation bots interfering with the US election – Nature
  39. Twitter Bots Poised to Spread Disinformation Before Election – The New York Times
  40. Researchers voice concern over spread of disinformation on social media about US poll campaigns – The Week
  41. Twitter Bots Promote Right-Wing Conspiracies, Paper Shows – Defense One
  42. Twitter Beware: That QAnon Account May Be a Bot – National Interest
  43. Twitter bots poised to spread disinformation before election – Forbes India
  44. Twitter Bots Poised to Unfold Disinformation Earlier than Election – Latest News
  45. Researchers voice concern over spread of disinformation on social media about US poll campaigns – DevDiscourse
  46. Researchers voice concern over spread of disinformation on social media about US poll campaigns – Outlook
  47. Researchers voice concern over spread of disinformation on social media about US poll campaigns – India TV
  48. Disinformation within the 2020 Presidential Election – Think It Positive
  49. Americans who seek political insight and information on Twitter should know – Snopes
  50. Study identifies thousands of Twitter bots amplifying conspiracy theories ahead of the U.S. elections – VentureBeat
  51. Watch out for this misinformation on election day – The World News
  52. USC study says bots and conspiracy theorists infest Twitter chatter around upcoming election – KNX Los Angeles (CBS Radio)
  53. Disinformation rules in buildup to US presidential elections – Oridessa Post
  54. Election 2020 chatter on Twitter busy with bots and conspiracy theorists – USC News
  55. How bots threaten to derail the 2020 U.S. elections – VentureBeat
  56. Social Media Used To Spread Coronavirus Disinformation, And Patient Groups Are Fighting Back – NPR
  57. Segregated communities of polarized Twitter users are shaping online conversations about COVID-19 – PsyPost
  58. Beware of Bots Amid Election Year and Coronavirus Pandemic – Reform Austin
  59. Who’s a Bot? Who’s Not? – The New York Times
  60. The epic battle against coronavirus misinformation and conspiracy theories – Nature
  61. AI can distinguish between bots and humans based on Twitter activity – New Scientist
  62. Laziness is sure sign it’s not a bot – The Times
  63. Bot or Not? AI looks at Twitter behavior to sort real accounts from fake – Digital Trends
  64. Laziness is the key human trait that tells us apart from artificially intelligent ‘bots’ on social media – Daily Mail
  65. Study reveals behavioral differences between bots and humans that could inform new machine learning algorithms – TechXplore
  66. Researchers develop AI-based system to detect Twitter bots – Gadgets Now
  67. Bot or not? A.I. looks at Twitter behavior to sort real accounts from fake – Brinkwire
  68. AI Can Distinguish Between Bots, Humans Based on Twitter Activity – Communications of the ACM
  69. What are the characteristics of human beings who have not been able to reproduce social media bots that continue to evolve like humans? – Gigazine
  70. AI study of Twitter bots reveals boredom is what separates us from machines – TNW
  71. What’s human and what’s not when we talk? – COSMOS
  72. Researchers train AI to spot difference between bots and human users on Twitter based on their activity patterns – Computing
  73. Tiredness could be ‘human signature’ used to detect bots on Twitter – E&T
  74. AI can spot a bear bot at 20 paces – Fudzilla
  75. Online Behavioral Signatures Aid Development of Bot Detection Software – Courthouse News Service
  76. Bot detector may now be able to see clear ‘human signature’ in tweets – SiliconRepublic
  77. Researchers train AI to detect Twitter bots – Indian Express Indulge
  78. Laziness is very important: it’s what makes us human, and what may help us stop online spam – India Times
  79. This AI can now detect Twitter bots: See how it works – India TV
  80. USC Researchers Release Public Coronavirus Twitter Set for Academics – USC
  81. How malicious Twitter bots evolve to evade detection – The Irish Times
  82. Twitter ‘Bots’ Becoming More ‘Human,’ Will Influence 2020 Presidential Election, New Research Study Says – Inquisitr
  83. As 2020 Election Nears, Twitter Bots Have Only Gotten Better at Seeming Human – AdWeek
  84. Social media bots becoming more human and difficult to detect, study shows – E&T
  85. Twitter Bots Are Becoming More Human-Like – DefenseOne
  86. Bots evolving to better mimic humans during elections – HelpNet Security
  87. Modern Politics: Social Media Bots Will Be Harder To Detect During 2020 Election – StudyFinds
  88. Fake Accounts On Social Media Now Able To Copy Human Behaviour – NewsGram
  89. Bots harder to discern from humans have multiplied in online ‘arms race’ – SiliconRepublic
  90. Get ready for more humanlike bots, better deep-fake videos and wall-to-wall disinformation in 2020 race – The Baltimore Sun
  91. Bots might prove harder to detect in 2020 elections – EurekAlert!
  92. Bots in the Twittersphere – PEW Research Center
  93. Social Media Bots Deceive E-cigarette Users – Scientific American
  94. Twitter bots were more active than previously known during the 2018 midterms – CNBC
  95. Majority of Twitter bots affecting US elections originated from Russia and Iran – Devdiscourse
  96. About 20% of election posts on Twitter last fall were ‘bots,’ study says – Breitbart
  97. Thousands of Twitter bots active during 2018 US mid-term elections – The Economic Times
  98. How Twitter bots get people to spread fake news – ScienceNews
  99. Study: It only takes a few seconds for bots to spread misinformation – ArsTecnica
  100. Bots actually target and pursue individual influencers – EurekAlert!
  101. The charge of the chatbots: how do you tell who’s human online? – The Guardian
  102. Facebook’s Secret Weapon for Fighting Election Interference: The Government – Bloomberg
  103. Surge in anonymous Asia Twitter accounts sparks bot fears – The Japan Times
  104. The endless game of cat and mouse with spammers – Eureka
  105. Fake news is about to get a lot worse. That will make it easier to violate human rights – The Washington Post
  106. The Big, Bad Bot Problem – The Ringer
  107. Twitter Cracks Down on Bot Abuse – How Stuff Works
  108. Conservatives amplified Russian trolls 30 times more often than liberals in 2016 – Vox
  109. US conservatives spread tweets by Russian trolls over 30 times more often than liberals – MIT Tech Review
  110. How to Stop Russia From Wrecking Election 2018 – Daily Beast
  111. Twitter has been ignoring its fake account problem for years – Columbia Journalism Review
  112. Twitter’s huge bot problem is out of the bag – CNET
  113. Putin’s Pro-Trump Trolls Just Targeted Hillary Clinton and Robert Mueller – Mother Jones
  114. Twitter urged firms to delete data during 2016 campaign – POLITICO
  115. Bot-hunting Twitter bot sniffs out bogus political tweets – TechCrunch
  116. This new Twitter account hunts for bots that push political opinions – Quartz
  117. Lies, statistics and Twitter – Millennium Post
  118. Social media bots are a real problem and California may regulate them – Medianama
  119. Watch: Five Ways the Internet Is Destroying Society – IEEE Electronics 360
  120. Ending fake news means changing how Wall Street values Facebook and Twitter – Quartz
  121. Trolls, bots and fake news: the mysterious world of social media manipulation – Newsweek
  122. Twitter Bots Distorted the 2016 Election—Including Many Likely From Russia – Mother Jones
  123. Researcher Emilio Ferrara talks about the rise of fake news and botnets – Tech Crunch
  124. These Scientists Wanted To Understand Twitter’s Bot Armies, So They Built Their Own – Fast Company
  125. Senator Slams Twitter’s Disclosure On Russian Meddling As ‘Inadequate On Every Level’ – Forbes
  126. Twitter’s Disclosure of Russian Activity Sparks Criticism From Lawmakers – The Wall Street Journal
  127. Twitter takes its turn in the Russian probe spotlight – Politico
  128. Twitter Says It Found 201 Russia-Linked Accounts That Aimed to Influence U.S. Election – Fox Business
  129. TWITTER STORMS – Civicist
  130. JACK DORSEY TAKES HIS TURN IN THE RUSSIA PROBE BARREL – Vanity Fair
  131. Fake News on Twitter Flooded Swing States That Helped Trump Win – Mother Jones
  132. Twitter to Testify Before Senate in Russia Probe – US News
  133. Researchers find that Twitter bots can be used for good – Tech Crunch
  134. Twitter Bots Can Encourage Decent Conduct, Not Just Fake News – News18
  135. Twitter bots for good: USC ISI study reveals how information spreads on social media – EurekAlert!
  136. Germany Election So Far Unaffected by ‘Fake News’ – Snopes
  137. Social media ‘bots’ tried to influence the U.S. election. Germany may be next – Science
  138. Computational propaganda poses challenge – Global Times
  139. Russia’s propaganda machine amplifies alt-right – The Hill
  140. #FireMcMaster, Not Damore: Twitter Bots Are Thriving, And They’re More Lethal Than Ever – Fast Company
  141. Why didn’t Macron leaks carry more clout in the French presidential election? – USC News
  142. The curious case of ‘Nicole Mincey,’ the Trump fan who may actually be a bot – The Washington Post
  143. Trump Thanked A ‘Supporter’ On Twitter, Then A Mystery Unraveled – A Plus
  144. Spreading fake news becomes standard practice for governments across the world – The Washington Post
  145. One in five bots sharing fake news during France’s presidential election were also involved in the United States’ – ZME Science
  146. Black-market bots, duped humans are responsible for derailing elections with fake news – ThinkProgress
  147. Study: Bots have turned Twitter into a powerful political disinformation platform – Venture Beat
  148. Fake news bots are so economical, you can use them over and over – Harvard NiemanLab
  149. Pro-Trump Twitter bots were also used to target Macron, research shows – The Verge
  150. There’s a Bit of Overlap Between Bots Trying to Manipulate American and French Elections – New York Magazine
  151. Research links pro-Trump, anti-Macron Twitter bots – The Hill
  152. The Same Twitter Bots That Helped Trump Tried to Sink Macron, Researcher Says – VICE
  153. How the Hashtag Is Changing Warfare – SIGNAL
  154. How Twitter Is Being Gamed to Feed Misinformation – New York Times
  155. ‘Something fishy’ is going on with Trump’s twitter account, researchers say – Washington Post
  156. Inside Russia’s Social Media War on America – TIME (cover story)
  157. The Twitter Bots Who Tried to Steal France – Daily Beast
  158. When Facebook and Instagram Think You’re Depressed – VICE
  159. Twitter Has a Serious Problem—And It’s Actually a Bigger Deal Than People Realize – Mother Jones
  160. Sleeping Beauties of Science – Scientific American
  161. Twitter Bot — or Not? – The New York Times
  162. After political Twitter bot revelation, are companies at risk? – Computer World
  163. Searching for proof of Amy – San Francisco Examiner
  164. News That 48 Million Of Twitter’s Users May Be Bots Could Impact Its Valuation – Forbes
  165. How to save Twitter, two pennies at a time – The Denver Post
  166. How Understanding Identity Can Help Avoid Fraudulent Traffic – DMNews
  167. Fake accounts scandal weighs on Twitter boss – The Times
  168. Pressure Grows on Twitter CEO Dorsey Amid Bot Scandal – The Street
  169. CMO Today: Marketers and Political Wonks Gather for SXSW – The Wall Street Journal
  170. Huge number of Twitter accounts are not operated by humans – ABC News
  171. Early Twitter investor Chris Sacca says he ‘hates’ the stock, calls bot issue ‘embarrassing’ – CNBC
  172. Up to 48 million Twitter accounts are bots, study says – CNET
  173. R u bot or not? – VICE
  174. New Machine Learning Framework Uncovers Twitter’s Vast Bot Population – VICE/Motherboard
  175. A Whopping 48 Million Twitter Accounts Are Actually Just Bots, Study Says – Tech Times
  176. 15 Percent Of Twitter Accounts May Be Bots [STUDY] – Value Walk
  177. Why the Rise of Bots is a Concern for Social Networks – Enterpreneuer
  178. Study reveals whopping 48M Twitter accounts are actually bots – CBS News
  179. Twitter is home to nearly 48 million bots, according to report – The Daily Dot
  180. As many as 48 million Twitter accounts aren’t people, says study – CNBC
  181. New Study Says 48 Million Accounts On Twitter Are Bots – We are social media
  182. Almost 48 million Twitter accounts are bots – Axios
  183. Twitter user accounts: around 15% or 48 million are bots [study] – The Vanguard
  184. Report: 48 Million Twitter Accounts Are Bots – Breitbart
  185. Rise of the TWITTERBOTS – Daily Mail
  186. 15 per cent of Twitter is bots, but not the Kardashian kind – The Inquirer
  187. 48 mn Twitter accounts are bots, says study – The Economic Times
  188. 9-15 per cent of Twitter accounts are bots, reveals study – Financial Express
  189. Nearly 48 million Twitter accounts are bots: study – Deccan herald
  190. Study: Nearly 48 Million Twitter Accounts Are Fake; Many Push Political Agendas – The Libertarian Republic
  191. As many as 48 million accounts on Twitter are actually bots, study finds – Sacramento Bee
  192. Study Reveals Roughly 48M Twitter Accounts Are Actually Bots – CBS DFW
  193. Up to 48 million Twitter accounts may be Bots – Financial Buzz
  194. Up to 15% of Twitter accounts are not real people – Blasting News
  195. Tech Bytes: Twitter is Being Invaded by Bots – WDIO Eyewitness News
  196. About 9-15% of Twitter accounts are bots: Study – The Indian Express
  197. Twitter Has Nearly 48 Million Bot Accounts, So Don’t Get Hurt By All Those Online Trolls – India Times
  198. Twitter May Have 45 Million Bots on Its Hands – Investopedia
  199. Bots run amok on Twitter – My Broadband
  200. 9-15% of Twitter accounts are bots: Study – MENA FN
  201. Up To 15 Percent Of Twitter Users Are Bots, Study Says – Vocativ
  202. 48 million active Twitter accounts could be bots – Gearbrain
  203. Study: 15% of Twitter accounts could be bots – Marketing Dive
  204. 15% of Twitter users are actually bots, study claims – MemeBurn
  205. Almost 48 million Twitter accounts are bots – Click Lancashire
  206. As many as 48 million or around 15% of Twitter accounts are bots – TechWorm
  207. Twitter Has an Overwhelming 48 Million Bot Accounts – GineersNow
  208. Data Mining Reveals the Rise of ISIS Propaganda on Twitter – MIT Technology Review
  209. Data Mining Technology Helped Analyze ISIS Rise to Power – iHLS
  210. As a conservative Twitter user sleeps, his account is hard at work – Washington Post
  211. How a Chicago man posts hundreds of pro-Trump tweets each day – Daily Herald
  212. You’ve probably been tricked by fake news and don’t know it – Science News
  213. Twitter Bots Favored Trump Leading Up to Election – U.S. News
  214. How the Bot-y Politic Influenced This Election – MIT Technology Review
  215. Facebook, Twitter & Trump – The New York Review of Books
  216. How Twitter bots played a role in electing Donald Trump – WIRED
  217. Twitter Bots Pollute Public’s Understanding of Politics – Newsweek
  218. How Twitter bots helped Donald Trump win the US presidential election – Arstechnica
  219. On Twitter, No One Knows You Are a Trump Bot – Fast Company
  220. The Algorithmic Democracy – Fast Co. Design
  221. Election 2016 Belongs to the Twitter Bots – VICE
  222. USC Study Finds Many Political Tweets Come From Fake Accounts – CACM News
  223. Almost a fifth of election chatter on Twitter comes from bots – Fusion
  224. Study reports that nearly 20% of election-related tweets were ‘algorithmically driven’ – Talking New Media
  225. How Twitter bots affected the US presidential campaign – The Conversation
  226. Advertising is driving social media-fuelled fake news and it is here to stay – The Conversation
  227. 20% of All Election Related Tweets Came From Non-Humans – Futurism
  228. Twitter Bots Dominate 2016 Presidential Election: New Study – Heavy
  229. Tracking The Election With Social Media In Real-Time: How Accurate Is It? – Heavy
  230. BOTS ‘SWAY’ ELECTION Fake tweets by social media robots could swing US Presidential election – The Sun
  231. A fifth of all US election tweets have come from bots – ABC News
  232. The Trump factor tipped to spread to Australian politics as Aussie Truthers push on social media – News .com.au
  233. There are 400,000 Bots That Just Tweet Political Views All Day – Investopedia
  234. Real, or not? USC study finds many political tweets come from fake accounts – Science Blog
  235. Software bots distort Donald Trump support on Twitter: Study – ETCIO
  236. How hackers, social bots, data analysts shaped the U.S. election – The Nation
  237. That swarm of political tweets in your feed? Many could be from bots – The Business Journals
  238. Software ‘bots’ distort Trump support on Twitter – New Vision
  239. Bots Invade Twitter, Spreads Misinformation On US Election – EconoTimes
  240. Software ‘bots’ seen skewing support for Trump on Twitter – The Japan Times
  241. US Presidential Elections 2016: Bot-generated fake tweets influencing US election outcome, says new study – Indian Express
  242. US elections 2016: Researchers show how Twitter bots are trying to influence the poll in favour of Trump – International Business Times
  243. Aliens, and the autopsy into Hillary Clinton’s political death – Toronto SUN
  244. Hillary vs Trump: Most of the election chatter online by Twitter bots, says study – Tech 2 First Post
  245. Twitter bots distort Trump support – iAfrica
  246. Social Media ‘Bots’ Working To Influence U.S. Election – CBS San Francisco
  247. Almost a fifth of election chatter on Twitter comes from bots – Full Act
  248. Software ‘bots’ distort Trump support on Twitter: study – Yahoo! News
  249. Bots Will Break 2016 US Elections Results – iTechPost
  250. Scientist Worries Robot-Generated Tweets Could Compromise The Presidential Election – Newsroom America
  251. Software ‘bots’ distort Trump support on Twitter: study – Phys.org
  252. Spotlight: Fake tweets endanger integrity of U.S. presidential election – XinhuanNet
  253. New Study: Twitter Bots Amount for One-Fifth of US Election Conversation – Dispatch Weekly
  254. Are Robot generated Tweets compromising US Polls? – TechRadar India
  255. Fake tweets endanger integrity of US presidential election – Global Times
  256. Software ‘bots’ distort Trump support on Twitter: study – The Daily Star
  257. Software ‘bots’ distort Trump support on Twitter: study – News Dog
  258. Malicious Twitter bots could have profound consequences for the election – RawStory
  259. ‘Robot-generated fake tweets influencing US election outcome’ – Daily News & Analysis
  260. Sophisticated Bot-Generated Tweets Could Influence Outcome of US Presidential Election – Telegiz
  261. UIC Journal Shows ‘Bots’ Sway Political Discourse, Could Impact Election – NewsWise
  262. Bot-generated tweets could threaten integrity of 2016 US presidential election: Study – BGR
  263. Bot generated tweets influence US Presidential election polls – I4U News
  264. High percentage of robot-generated fake tweets likely to influence public opinion – NewsGram
  265. ‘Robot-generated fake tweets influencing US election outcome’ – Press Trust of India
  266. Robot-generated fake tweets influencing US election outcome: Study – IndianExpress
  267. Fake Tweets, real consequences for the election – Phys.org
  268. Real, or not? USC study finds many political tweets come from fake accounts – USC News
  269. We’re in a digital world filled with lots of social bots – USC News
  270. 23 reasons to get excited about data – IBM Watson Analytics
  271. Algorithm knows when corporate money is pushing memes online – New Scientist
  272. Algorithm identifies artificially promoted Twitter memes and hashtags – The Stack
  273. La fórmula científica que te podría convertir en la próxima Cara Delevingne – Vanitatis
  274. Social Network Sleuths: Investigators Pursue Criminal Gangs Via Phone Chatter – Homeland Security Today
  275. The More You Comment Online, The Dumber Your Comments Become – Huffington Post
  276. The longer you’re on the web, the less interesting your commentary becomes – USC News
  277. Cool study, bro: Why Reddit comments degrade over time – USC Press Room
  278. On Twitter, your positive tweets are actually contagious – The Daily Dot
  279. Happiness is contagious – USC Viterbi News
  280. Pro-Trump Twitter Bots at Center of Nevada Mystery – Wall Street Journal
  281. How Ebola Infected Twitter: When it comes to sharing online, nothing spreads like fear – Nautilus
  282. Web of lies: Is the internet making a world without truth? – New Scientist
  283. The Top 100 Big Data Experts to Follow in 2016 – Maptive
  284. How DARPA Took On the Twitter Bot Menace with One Hand Behind Its Back – MIT Technology Review
  285. The US government held a contest to identify evil propaganda robots on Facebook and Twitter – Business Insider
  286. Why you need to purge your Twitter feed of angry people – The Telegraph
  287. Twitter Emotions Are Contagious, Says New Study, But At Least The Positive Ones Are More So Than The Negative Ones – Bustle
  288. Twitter users more likely to share happiness than sadness – The Rakyat Post
  289. Twitter reacts positively to upbeat emotions, study finds – USC News
  290. Positive emotions more contagious than negative ones on Twitter – Phys.org
  291. On Twitter, Is the Next POTUS a Bot-US? – Wall Street Journal
  292. Why Does Facebook Keep Suggesting You Friend Your Tinder Matches? – Vice
  293. New data suggest social media brings out the best in us, after all – Quartz
  294. Bad news travels fast but positive posts spread wide – The Straits Times
  295. Positive content has greater reach – Business First Magazine
  296. Data Shows that Positive Content Does Better on Social Media – Good
  297. Why can’t Twitter kill its bots? – Fusion
  298. The Algorithm of Instagram Fashion – The Science Times
  299. THE SCIENCE OF A SUPERMODEL – Vogue
  300. Here’s how to predict next season’s breakout stars – Dazed
  301. Instagram Can Determine Which Models Rule the Runway at Fashion Week – StyleCaster
  302. Instagram to predict next ‘It Girl’? – HLN Tv
  303. Wondering Who’ll Be This Season’s Breakout Models? Apparently There’s A Mathematical Formula For That – Grazia Daily
  304. Study Concludes Runway Models With Hips Have a Harder Time Being It Girls – Styleite
  305. FMD Featured in Indiana University Study to Predict Popular Models for NYFW – SBWire
  306. NYFW: Instagram May Be Able To Predict Fashion Week’s Top Models – University Herald
  307. Scientists Can Now Predict How Successful A Model Will Be – AskMen
  308. Stylebook snapshot: Researchers study impact of Instagram on models’ success – Pittsburg Post Gazette
  309. VIDEO: Instagram can predict top models for New York Fashion Week – Irish Examiner
  310. America’s Next Top Model Cycle 22 Winner Predicted By Instagram? Scientists Create Algorithm That Can Do That – iSchoolGuide
  311. FOLLOWING INSTAGRAM MODELS FOR SCIENCE AND FASHION WEEK – News Ledge
  312. Instagram Correctly Predicts 80% Of Next Top Models At Fashion Event – Yibada
  313. Instagram can now predict who America’s Next Top Model will be – Digital Trends
  314. INSTAGRAM WILL TELL YOU ABOUT TOP MODELS AT THE NEW YORK FASHION WEEK – The Market Business
  315. INSTAGRAM IS QUITE GOOD AT PREDICTING WHO THE NEXT TOP MODEL WILL BE – Regal Tribune
  316. Instagram can help predict a model’s success – Red Orbit
  317. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODEL – The Market Business
  318. INSTAGRAM CAN MAKE ACCURATE PREDICTIONS ON SUPERMODELS’ POPULARITY – Mirror Daily
  319. SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODEL – Wall Street Hedge
  320. NEW ALGORITHM CAN HELP INSTAGRAM PREDICT AMERICA’S NEXT TOP MODEL – Utah People’s Post
  321. Instagram can predict the NYFW next top model with 80 percent accuracy – Inferse
  322. Is Instagram the new runway for fashion? – Daily O
  323. How Instagram Can Predict Next Supermodels? – My Tech Bits
  324. INSTAGRAM WILL TELL YOU WHO IS THE NEXT TOP MODEL – Apex Tribune
  325. Algorithm using Instagram data can predict upcoming top model – Northern Californian
  326. NYFW: Instagram Could Predict The Next Top Model – University Herald
  327. Instagram Can Now Be Used to Predict the Fashion World’s Next Supermodel – iDigitalTimes Australia Instagram, Social Media, and New York Fashion Week – Pioneer News
  328. Instagram Predicts Future Of Modeling Popularity – Press Examiner
  329. Instagram Predicts A Model’s Future Popularity According To Social Scientists – Bustle
  330. IU SCIENTISTS CAN PREDICT AMERICA’S NEXT TOP MODEL USING INSTAGRAM – I4U
  331. Instagram Could Be Used To Identify Popularity Level Of Models – ubergizmo
  332. Instagram will tell you industry’s next top model – Nature World Report
  333. Next Year’s Fashion Trends: Indiana University Algorithm Employs Instagram Data To Predict The Next Top Models – Immortal News
  334. Popularity of models can be gauged using Instagram, study shows – Techienews
  335. INSTAGRAM CAN HELP PREDICT INDUSTRY’S NEXT TOP MODEL – The market business
  336. TOP MODELS’ SUCCESS NOW DEPENDS UPON THEIR INSTAGRAM POPULARITY – Trinity News Daily
  337. Who will be America’s next top model? Ask Instagram – CBS News
  338. This Machine-Learning Algorithm Can Predict the Next Top Model – The Fashion Spot
  339. New York Fashion Week 2015: Can Scientists Use Instagram To Identify Budding Models? – iDigitalTimes
  340. Want To Know If You Can Be A Fashion Model? There’s A Machine-Learning Algorithm For That – Tech Times
  341. SCIENTISTS CAN USE INSTAGRAM TO PREDICT FASHION WEEK’S BIGGEST MODELS – Harper’s Bazaar
  342. Scientists Can Now Predict Top Models. Sorry, Tyra – Yahoo! Style
  343. Scientists Figure Out a Formula to Determine Top Model Success – Racked
  344. Can You Scientifically Predict a Model’s Success? – New York Magazine
  345. Machine Learning Algorithm Predicts Which New Faces Will Make It as Fashion Models – MIT Technology Review
  346. Machine Learning Selects World’s Next Top Models – Communications of the ACM
  347. Slack Is Overrun With Bots. Friendly, Wonderful Bots – WIRED
  348. The science of SUPERMODELS: Researchers create algorithm that scours Instagram to find the best new talent – Daily Mail UK
  349. Machine learning selects world’s next top models – it News
  350. IU scientists use Instagram data to forecast top models at New York Fashion Week – IU Bloomington newsroom
  351. This new study suggests sad tweets make you sad – Fusion
  352. The Power Of Twitter’s Emotional Influence – Focus News
  353. Emotions in Tweets Are Contagious: Study – NDTV
  354. Emotions in tweets are contagious – Business Standard
  355. Emotions on Twitter are contagious, says study – DNA
  356. ‘Sleeping beauty’ papers slumber for decades – Nature News
  357. Even Einstein’s Research Can Take Time to Matter – New York Times
  358. ‘Sleeping beauty’ studies ahead of their time – ABC Science
  359. Like Sleeping Beauty, some research lies dormant for decades, study finds – Phys.org
  360. The Dayside : Kissed by a prince – Physics Today
  361. The Sleeping Beauties of Science – Pacific Standard
  362. Quando la ricerca è una “bella addormentata” – Le Scienze
  363. Paper all’avanguardia: fanno il botto decenni dopo la pubblicazione – Oggi Scienza
  364. ‘Sleeping Beauty’ studies don’t pay off for decades – Futurity
  365. Sleeping Beauty Research Papers Can Languish For Decades, Even For Albert Einstein – Tech Times
  366. Like Sleeping Beauty, Some Research Lies Dormant for Decades – News Wise
  367. El estudio de Einstein que resucitó a los 60 años y otras bellas durmientes – El Pais
  368. ‘Sleeping Beauty’ Studies Don’t Pay Off for Decades – Epoch Times
  369. Like Sleeping Beauty, some research lies dormant for decades, IU study finds – Indiana University Newsroom
  370. Bot or Not? By James Gleick – The New York Review of Books
  371. Twitter’s Bot Problem: Katy Perry, Taylor Swift, Justin Bieber, Rihanna And Other Musicians Have Mostly Fake Followings – International Business Times
  372. Why Fear Spreads Faster Than Facts on Social Media – Hootsuite
  373. In Social Networking, ‘Weak’ Connections May Be the Most Powerful – Vice.com
  374. Fear, Misinformation, and Social Media Complicate Ebola Fight – TIME
  375. Social media can improve, muddy election campaigns – Pittsburgh Tribune-Review
  376. How To Spot A Social Bot On Twitter – MIT Technology Review
  377. Barack Obama Is Probably a Robot, and Other Lessons from ‘Bot Or Not’ – Vice.com
  378. Social Bots on Twitter are More Than a Minor Nuisance – Social Times
  379. An Algorithm To Identify Social Bot on Twitter – Value Walk
  380. Lying, spamming and scamming on the web – The Spectator
  381. This Algorithm Tells You If A Twitter Account Is a Spam Bot – Mashable
  382. How to Spot A Bot… or Find Out If You Sound Like One – ABC News
  383. Lo strumento per distinguere bot e umani su Twitter – Wired.it
  384. Indiana University Will Devote $1 Million to the Study of Internet Memes – The Mary Sue
  385. The U.S. government is spending $1 million to figure out memes – The Daily Dot
  386. U.S. Military Sends Scouting Party Into the Twitterverse – TIME
  387. US military studied how to influence Twitter users in Darpa-funded research – The Guardian
  388. Twitter Inc Users Studied By US Military In Darpa-Funded Research – Value Walk
  389. How online ‘chatbots’ are already tricking you – BBC
  390. ‘Bot or Not’ App Susses Out Twitter Spambots – Tom’s Guide
  391. Computer scientists develop tool for uncovering bot-controlled Twitter accounts – Phys.org
  392. IU computer scientists develop tool for uncovering bot-controlled Twitter accounts – IU Newsroom
  393. Criminal Gang Connections Mapped via Phone Metadata – Communications of the ACM
  394. New software can map criminal gang connections – The Free Press Journal
  395. Gangster science: How police use network theory to track gang members – The Daily Dot
  396. New software can map criminal gang connections – Business Standard
  397. IU researcher helps Italian police fight crime – The Washington Times
  398. Criminal gang connections mapped via phone metadata – New Scientist
  399. Mafia Wars: How Italy’s Secret Police Use Metadata To Track Organized Crime – Fast Company
  400. LogAnalysis maps the structure of gangs using phone records – Engadget
  401. How to Detect Criminal Gangs Using Mobile Phone Data – MIT Technology Review
  402. Complex networks researcher at IU fighting crime with mobile phone data – IU Newsroom
  403. One Tweet if by Land – Newsweek
  404. Where do Twitter trends start? Try Cincinnati – The Washington Post
  405. Study: Seattle is top Twitter trendsetter in the U.S. – The Seattle Times
  406. The Top Five Trend-Setting Cities on Twitter – MIT Technology Review
  407. Study Finds Cincinnati Is Major Twitter Trendsetter in U.S. – CityBeat
  408. Seattle generates more nationally-trending topics on Twitter than any other U.S. city, study says – GeekWire
  409. Cincinnati is leading the way on Twitter – CincyBizBlog
  410. The Anatomy of the Occupy Wall Street Movement on Twitter – MIT Technology Review
  411. Data dance, big data and data mining – The Why Files
  412. Cell phone data analysis dials in crime networks – Science News
  413. Using statistics to catch cheats and criminals – Physics Today
  414. Bond with the best: FaceBook vs Twitter – TechKnowBits.com
  415. Study: Facebook Builds Better Communities Than Twitter – The Atlantic
  416. Facebook Builds Stronger Bonds Than Twitter, Study Says – Mashable
  417. Study shows similarities between Facebook and real-world communities – Leaders West
  418. Does Facebook Really Create Stronger Bonds Than Twitter? – Daily lounge
  419. Facebook Encourages Stronger Bonds Over Twitter: Study – hashtags.org
  420. Facebook and Strongly Connected Communities – Cornell University
  421. Driven by friendship – SpringerSelect
  422. Facebook is a community – Science Daily
  423. Data-Mining Facebook – Idiro Technologies

Press in non-English media

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