Kristina Lerman

A method for analyzing public emotions through social media data.

A study of public sentiment on Reddit following the October 2023 Hamas attack.

Examining how social media fuels eating disorders and their impact on individuals.

An analysis of political discussions and community interactions on Twitter.

This article examines bias in language models and their emotional alignment with different social groups.

This article examines how language models can adopt ideological biases from training data.

A study on how prior knowledge affects LLMs' ability to recognize emotions.

A look at how feelings shape political divides and decision-making.

SoMeR combines diverse user data for better online behavior insights.

Investigating how language models treat gender-queer language online.

Examining the effectiveness of counterspeech against hate communities online.

Analyzing language patterns to identify negative content in social media.

Examining how health experts and pseudo-experts communicated during the pandemic.

Examining gender dynamics in online body image conversations.

Exploring methods to align LLMs with online groups for better insights.

Researchers create a method to test interventions for eating disorders without real risks.

Examining the limits of language models in handling subjective tasks.

Analyzing changes in research activities during the COVID-19 pandemic.

An examination of evolving online narratives during the Russia-Ukraine war.

Examining fairness and bias in social media content recommendations.

Research shows how algorithms shape user views on social networks.

Discover how your friends influence your view of popularity and happiness.

Examining how U.S. cities have changed from 1900 to 2015.

Discover the rise of affective polarization and its impact on society.

Examining the support and harm of online spaces for eating disorders.