Hannah Mieczkowski

Hannah Mieczkowski

PhD Candidate in Communication

Stanford University

Biography

I am a PhD Candidate in Communication at Stanford University studying media psychology. I use survey-based, experimental and text analysis methods to investigate dyadic and group dynamics, social cognition, and language use in the area of human-machine communication, with a focus on AI. I am also interested in the conceptualization and measurement of digital media use.

Feel free to contact me via email (hnmiecz@stanford.edu) or Twitter (@hnmiecz).

Interests

  • Artificial Intelligence in Social Life
  • Human Machine Communication
  • Language Production and Comprehension
  • Interpersonal Perception
  • Relationships between Social Media and Well-being

Education

  • PhD in Communication, 2022

    Stanford University

  • MA in Communication, 2020

    Stanford University

  • BA in Psychology & BA in Linguistics, 2017

    Stony Brook University

Works Accepted and Under Review

Works denoted with an * have been accepted as a journal article, conference proceeding or conference paper.

Social Media and Well-being: A Methodological Perspective

We provide a review of five methodological developments poised to provide increased understanding in the domain of social media and well-being: (1) the use of longitudinal and experimental designs; (2) the adoption of behavioural (rather than self-report) measures of SMU; (3) a shift away from aggregate use; (4) the emergence of an idiographic media effects paradigm; and (5) the use of formal modelling and machine learning. (PsyArXiv Link)

Positioning AI-Mediated Communication in the Field of Human-Machine Communication*

I outline relevant theories of social cognition and presiding ideas surrounding language production and comprehension in conversation. Within these two broad components of communication, similarities and differences between human-machine communication (HMC) and AI-mediated communication (AI-MC) are investigated. (PDF - Workshop Paper)

Artificial intelligence in communication impacts language and social relationships

Two randomized experiments (n = 1036) provide evidence that a commercially deployed AI changes how people interact with and perceive one another in pro-social and anti-social ways. We find that even though AI can increase communication efficiency and improve interpersonal perceptions, it risks changing users’ language production and continues to be viewed negatively. (PDF - arXiv)

Applying the Principal-Agent Framework to AI-Mediated Communication: Psychological Implications*

We introduce the concept of principal-agent relationships to AI-Mediated Communication (AI-MC) and discuss its applications across the social sciences, focusing on the psychological implications.

Effects of AI Use on Interpersonal Perceptions of Job Applicants

To better understand the impact of AI in employment-related contexts, we conducted two experiments (the first pre-registered) investigating how the use of AI by applicants influences their job opportunities.

Social media use and psychological well-being: a meta-analysis*

Through a meta-analysis of 226 articles, we investigate the relationship between social media use and six types of well-being.

Research Experience

 
 
 
 
 

Research Intern, HCI

Dataminr

Jun 2021 – Sep 2021 New York, NY
  • Led research projects employing methodologies such as discovery interviews, hierarchical task analysis and prototype testing to learn about user experiences in human-AI collaborative environments
  • Leveraged research insights to provide product recommendations, as well as inform short-term and long-term roadmapping
  • Collaborated with product managers, designers, engineers and subject matter experts to determine product strategy
  • Created lo-fi designs in Figma for new automated features in internal Dataminr tools, which were then built out by the engineering team
 
 
 
 
 

UX Research Intern

Facebook

Jun 2020 – Sep 2020 Menlo Park, CA
  • Conducted in-depth interviews with users, which led to the shipment of several products for the Community Integrity teams
  • Collaborated with a team of designers, engineers, content strategists and product managers to provide solution-focused insights
  • Presented research findings to cross-functional stakeholders through long-form and short-form reports
  • Synthesized internal and external research in a literature review with recommendations for product changes
 
 
 
 
 

UX Researcher

PRO Unlimited @ Facebook

Jun 2019 – Jun 2020 Menlo Park, CA
  • Designed and performed cognitive testing on survey questions to measure sentiment towards Groups products
  • Analyzed behavioral and survey data to assess metrics regarding meaningful communities and continued use intentions.
  • Coded open-ended survey responses to examine textual correlates with positive and negative product experiences.
 
 
 
 
 

Research Assistant

PRO Unlimited @ Facebook

Jul 2018 – Nov 2018 Menlo Park, CA
  • Conducted large-scale literature reviews on motivations and consequences of using social media, as well as differences in perceptions of well-being across cultures.
  • Synthesized findings in two reviews of these topics and presented work and product recommendations to relevant stakeholders.
 
 
 
 
 

Doctoral Researcher

Social Media Lab, Stanford University

Sep 2017 – Present Stanford, CA
  • Managed multiple projects, working with senior scholars and mentoring undergraduate research assistants
  • Led teams of researchers in research question development, data collection and analysis, and publication
  • Presented research to interdisciplinary audiences with varying technical skill levels
  • Balanced stakeholder interests in both research and teaching settings
  • Integrated both quantitative (surveys, large-scale text analyses, experiments, meta-analyses) and qualitative (interviews) methods