Search Results for author:
Found 65 papers, 24 papers with code
Condolence and Empathy in Online Communities
Here, we develop computational tools to create a massive dataset of 11. 4M expressions of distress and 2. 8M corresponding offerings of condolence in order to examine the dynamics of condolence online.
SemEval-2022 Task 8: Multilingual news article similarity
Thousands of new news articles appear daily in outlets in different languages.
Learning PyTorch Through A Neural Dependency Parsing Exercise
Dependency parsing is increasingly the popular parsing formalism in practice.
Classification without (Proper) Representation: Political Heterogeneity in Social Media and Its Implications for Classification and Behavioral Analysis
Reddit is home to a broad spectrum of political activity, and users signal their political affiliations in multiple ways—from self-declarations to community participation.
Learning about Word Vector Representations and Deep Learning through Implementing Word2vec
Word vector representations are an essential part of an NLP curriculum.
The subtle language of exclusion: Identifying the Toxic Speech of Trans-exclusionary Radical Feminists
Toxic language can take many forms, from explicit hate speech to more subtle microaggressions.
When it Rains, it Pours: Modeling Media Storms and the News Ecosystem
Most events in the world receive at most brief coverage by the news media.
Aligning with Whom? Large Language Models Have Gender and Racial Biases in Subjective NLP Tasks
We find that for both tasks, model predictions are closer to the labels from White and female participants.
You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments
The versatility of Large Language Models (LLMs) on natural language understanding tasks has made them popular for research in social sciences.
Is "A Helpful Assistant" the Best Role for Large Language Models? A Systematic Evaluation of Social Roles in System Prompts
Commercial AI systems commonly define the role of the LLM in system prompts.
Social Meme-ing: Measuring Linguistic Variation in Memes
Much work in the space of NLP has used computational methods to explore sociolinguistic variation in text.
RCT Rejection Sampling for Causal Estimation Evaluation
We contribute a new sampling algorithm, which we call RCT rejection sampling, and provide theoretical guarantees that causal identification holds in the observational data to allow for valid comparisons to the ground-truth RCT.
Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamics
Linguistic style matching (LSM) in conversations can be reflective of several aspects of social influence such as power or persuasion.
Your spouse needs professional help: Determining the Contextual Appropriateness of Messages through Modeling Social Relationships
We introduce a new dataset of contextually-situated judgments of appropriateness and show that large language models can readily incorporate relationship information to accurately identify appropriateness in a given context.
When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset
Further, our work shows that backgrounds not previously considered in NLP (e. g., education), are meaningful and should be considered.
Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark
Large language models (LLMs) have been shown to perform well at a variety of syntactic, discourse, and reasoning tasks.
Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social Media
Social media enables the rapid spread of many kinds of information, from memes to social movements.
POTATO: The Portable Text Annotation Tool
We present POTATO, the Portable text annotation tool, a free, fully open-sourced annotation system that 1) supports labeling many types of text and multimodal data; 2) offers easy-to-configure features to maximize the productivity of both deployers and annotators (convenient templates for common ML/NLP tasks, active learning, keypress shortcuts, keyword highlights, tooltips); and 3) supports a high degree of customization (editable UI, inserting pre-screening questions, attention and qualification tests).
A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing
We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low construct validity and reproducibility.
Modeling Information Change in Science Communication with Semantically Matched Paraphrases
Whether the media faithfully communicate scientific information has long been a core issue to the science community.
SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis
We propose MINT, a new Multilingual INTimacy analysis dataset covering 13, 372 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese, Hindi, and Arabic.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications
Second, we show how our model identifies key contextual elements in a sentence that are likely to contribute most to a reader's understanding of the target word.
ByT5 model for massively multilingual grapheme-to-phoneme conversion
In this study, we tackle massively multilingual grapheme-to-phoneme conversion through implementing G2P models based on ByT5.
Networks and Identity Drive Geographic Properties of the Diffusion of Linguistic Innovation
In this study, we show that demographic identity and network topology are both required to model the diffusion of innovation, as they play complementary roles in producing its spatial properties.
Detecting Community Sensitive Norm Violations in Online Conversations
Online platforms and communities establish their own norms that govern what behavior is acceptable within the community.
Phone-to-audio alignment without text: A Semi-supervised Approach
The task of phone-to-audio alignment has many applications in speech research.
Measuring Sentence-Level and Aspect-Level (Un)certainty in Science Communications
Here, we introduce a new study of certainty that models both the level and the aspects of certainty in scientific findings.
An animated picture says at least a thousand words: Selecting Gif-based Replies in Multimodal Dialog
Online conversations include more than just text.
Ranked #1 on
Multimodal GIF Dialog
on GIF Reply Dataset
Using Sociolinguistic Variables to Reveal Changing Attitudes Towards Sexuality and Gender
The linguistic choices in each variable allow us to study increased rates of acceptances of gay marriage and gender equality, respectively.
Idiosyncratic but not Arbitrary: Learning Idiolects in Online Registers Reveals Distinctive yet Consistent Individual Styles
Furthermore, we provide a description of idiolects through measuring inter- and intra-author variation, showing that variation in idiolects is often distinctive yet consistent.
HamiltonDinggg at SemEval-2021 Task 5: Investigating Toxic Span Detection using RoBERTa Pre-training
In this paper, we demonstrate our system for detecting toxic spans, which includes expanding the toxic training set with Local Interpretable Model-Agnostic Explanations (LIME), fine-tuning RoBERTa model for detection, and error analysis.
MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting
In our work, we address this research gap by proposing a novel framework for CCA as a document-level context extraction and labeling task.
Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media
Online social media platforms increasingly rely on Natural Language Processing (NLP) techniques to detect abusive content at scale in order to mitigate the harms it causes to their users.
Modeling Framing in Immigration Discourse on Social Media
The framing of political issues can influence policy and public opinion.
The structure of online social networks modulates the rate of lexical change
Using Poisson regression and survival analysis, our study demonstrates that the community's network structure plays a significant role in lexical change.
Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations
Online conversations can go in many directions: some turn out poorly due to antisocial behavior, while others turn out positively to the benefit of all.
Audrey: A Personalized Open-Domain Conversational Bot
Conversational Intelligence requires that a person engage on informational, personal and relational levels.
Quantifying Intimacy in Language
Intimacy is a fundamental aspect of how we relate to others in social settings.
Finding Microaggressions in the Wild: A Case for Locating Elusive Phenomena in Social Media Posts
Microaggressions are subtle, often veiled, manifestations of human biases.
Wetin dey with these comments? Modeling Sociolinguistic Factors Affecting Code-switching Behavior in Nigerian Online Discussions
Multilingual individuals code switch between languages as a part of a complex communication process.
A Just and Comprehensive Strategy for Using NLP to Address Online Abuse
Online abusive behavior affects millions and the NLP community has attempted to mitigate this problem by developing technologies to detect abuse.
Demographic Inference and Representative Population Estimates from Multilingual Social Media Data
In a large experiment over multilingual heterogeneous European regions, we show that our demographic inference and bias correction together allow for more accurate estimates of populations and make a significant step towards representative social sensing in downstream applications with multilingual social media.
Still out there: Modeling and Identifying Russian Troll Accounts on Twitter
In this work, we: 1) develop machine learning models that predict whether a Twitter account is a Russian troll within a set of 170K control accounts; and, 2) demonstrate that it is possible to use this model to find active accounts on Twitter still likely acting on behalf of the Russian state.
Social and Information Networks Computers and Society
It's going to be okay: Measuring Access to Support in Online Communities
People use online platforms to seek out support for their informational and emotional needs.
Incorporating Dialectal Variability for Socially Equitable Language Identification
Language identification (LID) is a critical first step for processing multilingual text.
Citation Classification for Behavioral Analysis of a Scientific Field
Citations are an important indicator of the state of a scientific field, reflecting how authors frame their work, and influencing uptake by future scholars.
Annotating Characters in Literary Corpora: A Scheme, the CHARLES Tool, and an Annotated Novel
To address the latter problem, this work presents three contributions: (1) a comprehensive scheme for manually resolving mentions to characters in texts.
An analysis of ambiguity in word sense annotations
Word sense annotation is a challenging task where annotators distinguish which meaning of a word is present in a given context.
It's All Fun and Games until Someone Annotates: Video Games with a Purpose for Linguistic Annotation
Annotated data is prerequisite for many NLP applications.
