Research

The ultimate goal of my research is to uncover subtle acts of influence in strategic interactions across genders and any ensuing impacts on their performance evaluations and outcomes. Hence, I collect novel data sets from strategic interaction settings of inter-collegiate debate tournaments & MBA negotiation exchanges using text mining, argument mining and micro-econometric techniques. Further down my research agenda, I plan to employ natural language processing techniques in field experiments to understand heterogeneities in bargaining behavior and attitudes towards AI across social groups.

The (Great) Persuasion Divide? Gender Disparities in Debate Speeches & Evaluations

[paper available upon request] [slides]

Upcoming presentations: RES Annual Conference , AYEW Applied Young Economist Webinar, SOLE Society of Labor Economists Annual Conference, SMYE Spring Meeting of Young Economists 2021, ESPE European Society of Population Economics Annual Conference 2021

Presented at: : ETH Zurich Seminar in Economics & Data Science, AGEW Australian Gender Economic Workshop , Junior Americanist Workshop, Minerva Lab on Diversity & Gender Inequality, YSI – INET Plenary – “New Approaches to Old Questions : Current Debates in Feminist Economics” , YSI – INET Plenary – “Developing Countries: Challenges to Face Inequality “ , VfS Annual Conference – Gender Economics , Econometric Society World Congress , EALE SOLE AASLE World Conference 2020 , RGS Doctoral Conference in Economics (Dortmund), ESE Female Network Seminar (cyberspace), WUDC Gender Inclusion Panel Discussion (Bangkok), CBS Behavioral Working Group Seminar (New York), 2019 Econometric Society Winter Meeting (ESWM) (Rotterdam), Natural Language, Dialog and Speech Symposium of the New York Academy of Sciences (New York), CBS Chazen Institute Research Scholar Seminar (New York), Data Science Institute Poster Session (New York), Zurich Text As Data Workshop (Zurich), International Association of Applied Econometrics 2019 (Nicosia), TIBER Symposium on Psychology & Economics (Tilburg), Eastern European Machine Learning Summer School 2019 (Bucharest), Data Science Summer School 2018 (Paris), EUR Brownbag Seminar 2019, EUR Diversity Research Seminar 2018

Do men and women persuade differently? Are they evaluated differently? Using a novel data set of 1517 speech transcripts, evaluation scores and demographic data from highest-profile intervarsity debate tournaments, this research investigates spoken verbal tactics across genders and any ensuing impacts on their performance evaluations. I find significant variation in speech patterns of male and female speakers. Specifically, female speakers use more personal and disclosing speaking style, with more hedging phrases and disfluencies in their speeches. In their answers to questions from opponents during their speeches, they negate less while having notably longer and more vague answers. Evaluation-wise, within debates, except for disfluencies, there is no robust evidence of gender-specific evaluation standards. These findings suggest that women receive lower scores than men because their speeches contain more score-reducing and fewer score-enhancing features, rather than discrimination.

Gender Composition of Evaluation Committees and Speech Evaluation: Evidence from Debate Tournaments

[paper available upon request]

Upcoming presentation: EALE European Society of Labor Economists Conference

Does the gender composition of committees matter in evaluating persuasive speeches? This research exploits the random composition of 4896 evaluation panels to understand the causal impact of women on committees on debate performance evaluation of female vs. male speakers in the European and World Universities Debate Championships. On average, female speakers receive significantly lower scores than male speakers. Committees with a female chair judge are harsher to both male and female speakers, particularly in higher-ranked debates. The gender of other committee members does not affect evaluations. While accomplished male chair judges are more generous in scoring, they are significantly less so towards female speakers. Overall, these results suggest that gender quotas on evaluation committees does not necessarily eliminate the glass ceiling for women.

Acoustic-Prosodic, Lexical and Demographic Cues to Persuasiveness in Competitive Debate Speeches (with Ralph Vente, Sarah Ita Levitan, David Lupea and Julia Hirschberg)

[submitted]

1st Prize STAR Presentation Award, NYAS NDS2020 (cyberspace)

Presented at: STAR Talk @ Natural Language, Dialogue and Speech Symposium of the New York Academy of Sciences (cyberspace)

Using a data set of 674 audio profiles, transcripts, evaluation scores and demographic data of professional debate tournament speeches, we analyze the acoustic-prosodic and lexical correlates of persuasiveness, taking into account speaker, judge and debate characteristics to predict what matters for persuasiveness for male vs. female. Debate tournaments provide a useful means of systematically answering these questions because they include: (i) a diverse pool of intrinsically motivated professional debaters; (ii) exogenously assigned speaking position, topic and opponents; (iii) transparent evaluation criteria, based entirely on comparative argumentation strength; and (iv) accountable, selective panels of judges. We conduct 10-fold cross validation regression experiments to predict the persuasiveness of all speeches, as well as how different feature combination matters across genders. Overall, lexical features, i.e. word complexity, nouns, fillers and hedges, are the most predictive features of speech persuasiveness. The gender composition of judge panels and opponents play an important role in predicting speech scores. In combination with speaker and debate room characteristics, we achieved an R^2 of 0.4. Different lexical features matter differently for male vs. female speakers, yet there is no conclusive answer acoustic-wise for female speakers.

Gender Differences in Negotiation Tactics -A Text Mining Approach (with Malia Mason)

[data analysis in progress]

Building on recent work using text as data to study politeness and receptiveness in negotiations, we employ dictionary-based text mining techniques on a set of 1000 e-mail & 180 face-to-face negotiation exchanges among MBA professionals to uncover gender disparities in negotiation tactics. Preliminary findings in the face-to-face negotiation exchanges show that women across the board use significantly more polite language, indirect questions and hedges, as compared to men. By correlating these linguistic features to individual’s professional industry, personality measures and dyad-specific negotiation outcomes, we discuss the effectiveness of negotiation strategies for each gender, in both integrative and distributive negotiation contexts.

Choking in Male-dominated Rooms? Gender Composition of Opponents and Debate Performance

[data analysis in progress]

AI Judge in European Courts? A Vignette & Deliberation Experiment (with Lydia Mechtenberg, Hendrik Hüning and Arna Wömmel)

[experiment design completed]

OTHER RESEARCH

Two of a Kind Try Together? The Impact of Homophily on Innovation Decisions in Teams (with Josse Delfgaauw)

Accessit Best Paper Award at 16th Institutional & Organizational Academy 2017 (Corsica)

Presented at: 33rd European Economic Association Annual Meeting (Cologne), 3rd Lectures on Organizational Economics & Human Resources (Cologne), TI PhD Seminar, EUR Brownbag Seminar

The tendency to disproportionately interact with similar others (i.e. homophily) is a ubiquitous social phenomenon. While it is commonly hypothesized that homophily hampers group creativity and innovation, empirical findings are mixed. This research examines the impact of homophily on innovation in teams, in a simple setting where agents decide whether or not to implement a project that embodies strategic complementarity. Agents receive conditionally correlated private signals about the innovation quality, where homophily is the degree of correlation between the signals. Our key result is as follows: When agents share information truthfully, homophily reduces the probability of implementation; whereas the opposite occurs without information sharing. Given these effects, we discuss an alternative interpretation of homophily as correlated benefits and several extensions in correlation neglect, information collection behavior and strategic communication within the organizational context.

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