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Show Results For
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All HBS Web
(1,230)
- People (3)
- News (243)
- Research (611)
- Events (7)
- Multimedia (3)
- Faculty Publications (167)
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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...
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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.
- 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...
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Keywords:
User Generated Content;
Crowdsourcing;
Yelp;
Social and Collaborative Networks;
Information;
Internet and the Web;
Learning;
Mathematical Methods;
E-commerce
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.
- 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...
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Keywords:
Ad-sponsored Business Models;
Media Content;
Blog;
Revenue Sharing;
User-generated Content;
Platform-based Markets;
Blogs;
Business Model;
Digital Platforms;
Commercialization;
Digital Marketing
Sun, Monic, and Feng Zhu. "Ad Revenue and Content Commercialization: Evidence from Blogs." Management Science 59, no. 10 (October 2013): 2314–2331.
- 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...
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Keywords:
Negative Press;
Twitter;
Political Affiliation;
Affect;
News;
Media;
Internet and the Web;
Emotions;
Perspective;
Social Media
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.
The Content Trap
Companies everywhere face two major challenges today: getting noticed and getting paid. To confront these obstacles, Bharat Anand examines a range of businesses around the world, from Chinese Internet giant Tencent to Scandinavian digital trailblazer Schibsted,... View Details
- 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
- 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...
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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...
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Keywords:
Business Model;
Network Effects;
Mergers and Acquisitions;
Valuation;
Risk and Uncertainty
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
Ad Revenue and Content Commercialization: Evidence from Blogs
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
- 19 Oct 2021
- News
In the Contest for Content
Courtesy Sherrese Clarke Soares Courtesy Sherrese Clarke Soares As the founder and CEO of HarbourView Equity Partners, Sherrese Clarke Soares (MBA 2004) is establishing herself within the high-stakes contest to own the catalogs of music that attract View Details
- 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...
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Keywords:
AI;
Artificial Intelligence;
Model;
Hardware;
Data Centers;
AI and Machine Learning;
Applications and Software;
Analytics and Data Science;
Value
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...
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- 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...
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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...
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- 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....
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- 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...
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Keywords:
Information Technology;
Service Delivery;
Consumer Behavior;
Television Entertainment;
Service Industry;
Media and Broadcasting Industry
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.
- 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...
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Keywords:
Blockchain;
User Experience;
Digital Platforms;
Network Effects;
Internet and the Web;
Competition;
Web Services Industry
Esber, Jad, and Scott Duke Kominers. "Why Build in Web3." Harvard Business Review Digital Articles (May 16, 2022).
- August 2019
- Article
When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation
By: Yicheng Song, Nachiketa Sahoo and Elie Ofek
Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,...
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Keywords:
Recommender Systems;
Personalization;
Recommendation Diversity;
Variety Seeking;
Collaborative Filtering;
Consumer Utility Models;
Digital Media;
Clickstream Analysis;
Learning-to-rank;
Consumer Behavior;
Media;
Customization and Personalization;
Strategy;
Mathematical Methods
Song, Yicheng, Nachiketa Sahoo, and Elie Ofek. "When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation." Management Science 65, no. 8 (August 2019): 3737–3757.