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- All HBS Web
(1,557)
- People (3)
- News (355)
- Research (969)
- Events (3)
- Multimedia (1)
- Faculty Publications (255)
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- August 2017 (Revised December 2018)
- Case
Tamarin App: Natural Language Processing
By: Srikant M. Datar and Caitlin N. Bowler
In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This... View Details
Keywords: Data Science; Branding; Data Analytics; Analytics and Data Science; Brands and Branding; Analysis; Perception; Planning
Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised December 2018.)
- 2022
- Working Paper
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- 2025
- Working Paper
Partisan Corporate Speech
By: William Cassidy and Elisabeth Kempf
We construct a novel measure of partisan corporate speech using natural language
processing techniques and use it to establish three stylized facts. First, the volume
of partisan corporate speech has risen sharply between 2012 and 2022. Second, this
increase has... View Details
Keywords: Natural Language Processing; Perspective; Communication; Public Opinion; Business and Shareholder Relations; Trends
Cassidy, William, and Elisabeth Kempf. "Partisan Corporate Speech." Harvard Business School Working Paper, No. 05-056, May 2025.
- January–February 2025
- Article
The Double-Edged Sword of Exemplar Similarity
By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details
Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science 36, no. 1 (January–February 2025): 121–144.
- 2020
- Working Paper
Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation
By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details
Keywords: Natural Language Processing; Interpersonal Communication; Perspective; Decision Making; Perception
Yeomans, Michael, and Alison Wood Brooks. "Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation." Harvard Business School Working Paper, No. 20-077, February 2020.
- September 2017 (Revised March 2023)
- Background Note
Production Processes
By: Willy Shih and Michael W. Toffel
This note describes four broad categories of process architectures and then examines the nature of task assignment that typically would be found in a factory organized along the lines of each process type. It then delves more deeply into work flow policies, materials... View Details
Keywords: Production Management; Production Planning; Production Scheduling; Process Analysis; Process Maps; Processing Times; Process Improvement; Production; Management; Product; Consumer Products Industry; Manufacturing Industry
Shih, Willy, and Michael W. Toffel. "Production Processes." Harvard Business School Background Note 618-023, September 2017. (Revised March 2023.)
- June 2016
- Article
Understanding Online Hotel Reviews Through Automated Text Analysis
By: Shawn Mankad, Hyunjeong "Spring" Han, Joel Goh and Srinagesh Gavirneni
Customer reviews submitted at Internet travel portals are an important yet underexplored new resource in obtaining feedback on customer experience for the hospitality industry. These data are often voluminous and unstructured, presenting analytical challenges for... View Details
Keywords: Hotel Reviews; Natural Language Processing; Information Technology; Service Operations; Accommodations Industry; Moscow
Mankad, Shawn, Hyunjeong "Spring" Han, Joel Goh, and Srinagesh Gavirneni. "Understanding Online Hotel Reviews Through Automated Text Analysis." Service Science 8, no. 2 (June 2016): 124–138.
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
- February 2021
- Article
Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning
By: Sooji Ha, Daniel J Marchetto, Sameer Dharur and Omar Isaac Asensio
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to mitigate GHG emissions.... View Details
Keywords: Natural Language Processing; Analytics and Data Science; Environmental Sustainability; Infrastructure; Transportation; Policy
Ha, Sooji, Daniel J Marchetto, Sameer Dharur, and Omar Isaac Asensio. "Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning." Art. 100195. Patterns 2, no. 2 (February 2021).
- Article
The Lives and Deaths of Jobs: Technical Interdependence and Survival in a Job Structure
By: Sharique Hasan, John-Paul Ferguson and Rembrand Koning
Prior work has considered the properties of individual jobs that make them more or less likely to survive in organizations. Yet little research examines how a job’s position within a larger job structure affects its life chances and thus the evolution of the... View Details
Hasan, Sharique, John-Paul Ferguson, and Rembrand Koning. "The Lives and Deaths of Jobs: Technical Interdependence and Survival in a Job Structure." Organization Science 26, no. 6 (November–December 2015): 1665–1681.
- August 29, 2023
- Article
The Fragility of Artists’ Reputations from 1795 to 2020
By: Letian Zhang, Mitali Banerjee, Shinan Wang and Zhuoqiao Hong
This study explores the longevity of artistic reputation. We empirically examine whether artists are more- or less-venerated after their death. We construct a massive historical corpus spanning 1795 to 2020 and build separate word-embedding models for each five-year... View Details
Zhang, Letian, Mitali Banerjee, Shinan Wang, and Zhuoqiao Hong. "The Fragility of Artists’ Reputations from 1795 to 2020." Proceedings of the National Academy of Sciences 120, no. 35 (August 29, 2023).
- Article
Conversational Receptiveness: Expressing Engagement with Opposing Views
By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then... View Details
Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management
Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
- 2024
- Working Paper
Scaling Core Earnings Measurement with Large Language Models
By: Matthew Shaffer and Charles CY Wang
We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
Keywords: Large Language Models; AI and Machine Learning; Accounting; Profit; Corporate Disclosure; Analytics and Data Science; Measurement and Metrics
Shaffer, Matthew, and Charles CY Wang. "Scaling Core Earnings Measurement with Large Language Models." Working Paper, November 2024.
- March 2023
- Article
Authentic First Impressions Relate to Interpersonal, Social, and Entrepreneurial Success
By: David M. Markowitz, Maryam Kouchaki, Francesca Gino, Jeffrey T. Hancock and Ryan L. Boyd
This paper examines how verbal authenticity influences person perception. Our work combines human judgments and natural language processing to suggest verbal authenticity is a positive predictor of interpersonal interest (Study 1: 294 dyadic conversations), engagement... View Details
Keywords: Authenticity; Impression Formation; Natural Language Processing; First Impressions; Communication; Perception; Success
Markowitz, David M., Maryam Kouchaki, Francesca Gino, Jeffrey T. Hancock, and Ryan L. Boyd. "Authentic First Impressions Relate to Interpersonal, Social, and Entrepreneurial Success." Social Psychological & Personality Science 14, no. 2 (March 2023): 107–116.
- September 2017
- Article
It Doesn't Hurt to Ask: Question-asking Increases Liking
By: K. Huang, M. Yeomans, A.W. Brooks, J. Minson and F. Gino
Conversation is a fundamental human experience, one that is necessary to pursue intrapersonal and interpersonal goals across myriad contexts, relationships, and modes of communication. In the current research, we isolate the role of an understudied conversational... View Details
Keywords: Question-asking; Liking; Responsiveness; Conversation; Natural Language Processing; Interpersonal Communication; Behavior
Huang, K., M. Yeomans, A.W. Brooks, J. Minson, and F. Gino. "It Doesn't Hurt to Ask: Question-asking Increases Liking." Journal of Personality and Social Psychology 113, no. 3 (September 2017): 430–452.
- 2017
- Working Paper
The Need for Speed: Effects of Uncertainty Reduction in Patenting
By: Mike Horia Teodorescu
Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,... View Details
- 2022
- Working Paper
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details
Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations
Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
- 2017
- Working Paper
Machine Learning Methods for Strategy Research
By: Mike Horia Teodorescu
Numerous applications of machine learning have gained acceptance in the field of strategy and management research only during the last few years. Established uses span such diverse problems as strategic foreign investments, strategic resource allocation, systemic risk... View Details
Keywords: Machine Learning; Natural Language Processing; Classification; Decision Trees; Strategic Decisions; Strategy; Research; Information Technology
Teodorescu, Mike Horia. "Machine Learning Methods for Strategy Research." Harvard Business School Working Paper, No. 18-011, August 2017. (Revised October 2017.)
- November 2022
- Article
A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups
By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava
When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining... View Details
Keywords: Culture; Machine Learning; Natural Language Processing; Symbolic Boundaries; Organizations; Boundaries; Social Psychology; Interpersonal Communication; Organizational Culture
Bhatt, Anjali M., Amir Goldberg, and Sameer B. Srivastava. "A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups." Sociological Methods & Research 51, no. 4 (November 2022): 1681–1720.