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  • All HBS Web  (1,243)
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    • News  (272)
    • Research  (628)
    • Events  (10)
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  • Article

Pattern Detection in the Activation Space for Identifying Synthesized Content

By: Celia Cintas, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III and Komminist Weldemariam
Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize high-quality content at a large scale brings potential risks as the generated samples may... View Details
Keywords: Subset Scanning; Generative Models; Synthetic Content Detection
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Cintas, Celia, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III, and Komminist Weldemariam. "Pattern Detection in the Activation Space for Identifying Synthesized Content." Pattern Recognition Letters 153 (January 2022): 207–213.
  • 2005
  • Other Unpublished Work

Next Generation Learning via Next Generation Content

By: D. Quinn Mills
Keywords: Information Technology; Learning
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Mills, D. Quinn. "Next Generation Learning via Next Generation Content." MindEdge Press White Paper Series, MindEdge Press, Waltham, MA, December 2005.
  • 2025
  • Working Paper

Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs

By: Mengjie Cheng, Elie Ofek and Hema Yoganarasimhan
We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy. Using news articles from The New York... View Details
Keywords: Large Language Models; Content Creation; Media; Polarization; Generative Ai; Direct Preference Optimization; AI and Machine Learning; News; Perspective; Digital Marketing; Policy; Media and Broadcasting Industry
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Cheng, Mengjie, Elie Ofek, and Hema Yoganarasimhan. "Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs." Harvard Business School Working Paper, No. 25-051, April 2025.
  • October 2013
  • Article

Ad Revenue and Content Commercialization: Evidence from Blogs

By: Monic Sun and Feng Zhu
Many scholars argue that when incentivized by ad revenue, content providers are more likely to tailor their content to attract "eyeballs," and as a result, popular content may be excessively supplied. We empirically test this prediction by taking advantage of the... View Details
Keywords: Ad-sponsored Business Models; Media Content; Blog; Revenue Sharing; User-generated Content; Platform-based Markets; Blogs; Business Model; Digital Platforms; Commercialization; Digital Marketing
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Sun, Monic, and Feng Zhu. "Ad Revenue and Content Commercialization: Evidence from Blogs." Management Science 59, no. 10 (October 2013): 2314–2331.
  • September 2018
  • Article

Aggregation of Consumer Ratings: An Application to Yelp.com

By: Weijia Dai, Ginger Jin, Jungmin Lee and Michael Luca
Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in... View Details
Keywords: User Generated Content; Crowdsourcing; Yelp; Social and Collaborative Networks; Information; Internet and the Web; Learning; Mathematical Methods; E-commerce
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Dai, Weijia, Ginger Jin, Jungmin Lee, and Michael Luca. "Aggregation of Consumer Ratings: An Application to Yelp.com." Quantitative Marketing and Economics 16, no. 3 (September 2018): 289–339.
  • December 2021
  • Article

Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly

By: Andrea Bellovary, Nathaniel Young and Amit Goldenberg
Negativity has historically dominated news content; however, little research has examined how news organizations use affect on social media, where content is generally positive. In the current project we ask a few questions: Do news organizations on Twitter use... View Details
Keywords: Negative Press; Twitter; Political Affiliation; Affect; News; Media; Internet and the Web; Emotions; Perspective; Social Media
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Bellovary, Andrea, Nathaniel Young, and Amit Goldenberg. "Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly." Affective Science 2, no. 4 (December 2021): 391–396.
  • Research Summary

Social media and user-generated content

In this project, Professor Piskorski, jointly with Andreea Gorbatai, examines inherent trade-offs in provision of user-generated content, using Wikipedia as a research setting. In Wikipedia, every user has the right to add material to an article, but with no... View Details

  • May 2024
  • Supplement

HubSpot and Motion AI (B): Generative AI Opportunities

By: Jill Avery
The technologies driving artificial intelligence (AI) had progressed significantly since HubSpot’s acquisition of Motion AI in 2017. Generative AI was the newest major development. Software-as-a-service (SaaS) companies such as HubSpot were analyzing how generative AI... View Details
Keywords: Artificial Intelligence; CRM; Chatbots; Sales Management; Generative Ai; SaaS; Marketing; Sales; AI and Machine Learning; Customer Relationship Management; Applications and Software; Technological Innovation; Competitive Advantage; Technology Industry; United States
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Avery, Jill. "HubSpot and Motion AI (B): Generative AI Opportunities." Harvard Business School Supplement 524-088, May 2024.
  • 2016
  • Book

The Content Trap: A Strategist's Guide to Digital Change

By: Bharat Anand
Companies everywhere face two major challenges today: getting noticed and getting paid. To confront these obstacles, I examine a range of businesses around the world, from Chinese Internet giant Tencent to Scandinavian digital trailblazer Schibsted, from The New... View Details
Keywords: Networks; Information Technology; Organizational Change and Adaptation; Business Strategy
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Anand, Bharat. The Content Trap: A Strategist's Guide to Digital Change. New York: Random House, 2016.
  • May–June 2021
  • Article

Capturing Value in Platform Business Models that Rely on User-Generated Content

By: Hemang Subramanian, Sabyasachi Mitra and Sam Ransbotham
Business models increasingly depend on inputs from outside traditional organizational boundaries. For example, platforms that generate revenue from advertising, subscription, or referral fees often rely on user-generated content (UGC). But there is considerable... View Details
Keywords: Business Model; Network Effects; Mergers and Acquisitions; Valuation; Risk and Uncertainty
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Subramanian, Hemang, Sabyasachi Mitra, and Sam Ransbotham. "Capturing Value in Platform Business Models that Rely on User-Generated Content." Organization Science 32, no. 3 (May–June 2021): 804–823.
  • 24 Jul 2006
  • Research & Ideas

How Kayak Users Built a New Industry

settings. They cried out for a theoretical explanation. So Eric von Hippel, Christoph Hienerth, and I teamed up to see if we could construct a theory to explain the phenomena. Q: Can you describe in general the pathways View Details
Keywords: by Sean Silverthorne; Entertainment & Recreation
  • July 2023 (Revised July 2023)
  • Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
  • 14 Sep 2009
  • Research & Ideas

Understanding Users of Social Networks

Only difference: Piskorski has spent years studying users of online social networks (SN) and has developed surprising findings about the needs that they fulfill, how men and women use these services differently, and how Twitter—the newest... View Details
Keywords: by Sean Silverthorne; Advertising; Publishing
  • July 2023
  • Article

Negative Expressions Are Shared More on Twitter for Public Figures Than for Ordinary Users

By: Jonas P. Schöne, David Garcia, Brian Parkinson and Amit Goldenberg
Social media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with... View Details
Keywords: Social Media; Emotions
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Schöne, Jonas P., David Garcia, Brian Parkinson, and Amit Goldenberg. "Negative Expressions Are Shared More on Twitter for Public Figures Than for Ordinary Users." PNAS Nexus 2, no. 7 (July 2023).
  • 31 Mar 2014
  • Research & Ideas

Encouraging Niche Content in an Ad-Driven World

As the quantity of online content continues to proliferate—from cute cat videos to policy experts blogging on the Middle East—the consumer's expectation that online content should be free becomes more... View Details
Keywords: by Julia Hanna; Information; Publishing; Journalism & News
  • 20 Oct 2014
  • Research & Ideas

Users Love Ello, But What’s the Business Model?

that social media users are increasingly attracted to the idea of such a model. But funding it without advertising's help won't be easy. Two digital marketing experts, Harvard Business School professors John Deighton, the Harold M.... View Details
Keywords: Re: John A. Deighton & Sunil Gupta; Publishing; Financial Services
  • Summer 2017
  • Article

Measuring Consumer Preferences for Video Content Provision via Cord-Cutting Behavior

By: Jeffrey Prince and Shane Greenstein
The television industry is undergoing a generational shift in structure; however, many demand-side determinants are still not well understood. We model how consumers choose video content provision among over-the-air (OTA), paid subscription to cable or satellite, and... View Details
Keywords: Information Technology; Service Delivery; Consumer Behavior; Television Entertainment; Service Industry; Media and Broadcasting Industry
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Prince, Jeffrey, and Shane Greenstein. "Measuring Consumer Preferences for Video Content Provision via Cord-Cutting Behavior." Journal of Economics & Management Strategy 26, no. 2 (Summer 2017): 293–317.
  • 03 Sep 2024
  • Research & Ideas

Is It Even Possible to Dam the Flow of Misleading Content Online?

of moderating controversial content of all kinds. How much do users trust tech companies? The coauthors relied on a mathematical model to study strategic interactions, testing outcomes under different... View Details
Keywords: by Jay Fitzgerald; Information Technology; Technology
  • Article

Why Build in Web3

By: Jad Esber and Scott Duke Kominers
A major change is coming to the internet. While today’s dominant platforms have guarded their troves of user data and maintained an advantage through network effects, new companies—working in what they're calling a “Web3” model—are proposing a new value proposition to... View Details
Keywords: Blockchain; User Experience; Digital Platforms; Network Effects; Internet and the Web; Competition; Web Services Industry
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Esber, Jad, and Scott Duke Kominers. "Why Build in Web3." Harvard Business Review Digital Articles (May 16, 2022).
  • March 2005
  • Background Note

Home Video Games: Generation Seven

By: Elie Ofek
Discusses the issues facing firms in the seventh generation of home video game platforms. In particular, Sony and Microsoft plan to launch new game consoles in the 2005 to 2006 time frame. Each firm seems to be following a different strategy. Microsoft wants to launch... View Details
Keywords: Marketing Strategy; Competitive Strategy; Technological Innovation; Information Infrastructure; Applications and Software; Entertainment and Recreation Industry; Information Technology Industry
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Ofek, Elie. "Home Video Games: Generation Seven." Harvard Business School Background Note 505-072, March 2005.
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