Search Results for author:
Found 21 papers, 13 papers with code
Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance
We investigate the performance of LLM-based zero-shot stance detection on tweets.
Labor Space: A Unifying Representation of the Labor Market via Large Language Models
The labor market is a complex ecosystem comprising diverse, interconnected entities, such as industries, occupations, skills, and firms.
Cooperation and interdependence in global science funding
Investments in research and development are key to scientific and economic growth and to the well-being of society.
Discovering collective narratives shifts in online discussions
Narrative is a foundation of human cognition and decision making.
Can we trust the evaluation on ChatGPT?
ChatGPT, the first large language model (LLM) with mass adoption, has demonstrated remarkable performance in numerous natural language tasks.
Residual2Vec: Debiasing graph embedding with random graphs
Here, we investigate the impact of the random walks' bias on graph embedding and propose residual2vec, a general graph embedding method that can debias various structural biases in graphs by using random graphs.
Characterizing Partisan Political Narrative Frameworks about COVID-19 on Twitter
Here, taking the Democratic and Republican political social media posts about the pandemic as a case study, we demonstrate that a combination of computational methods can provide useful insights into the different contexts, framing, and characters and relationships that construct their narrative frameworks which individual posts source from.
People, Places, and Ties: Landscape of social places and their social network structures
Due to their essential role as places for socialization, "third places" - social places where people casually visit and communicate with friends and neighbors - have been studied by a wide range of fields including network science, sociology, geography, urban planning, and regional studies.
Unsupervised embedding of trajectories captures the latent structure of scientific migration
Here, we demonstrate the ability of the model word2vec to encode nuanced relationships between discrete locations from migration trajectories, producing an accurate, dense, continuous, and meaningful vector-space representation.
Persona2vec: A Flexible Multi-role Representations Learning Framework for Graphs
Graph embedding techniques, which learn low-dimensional representations of a graph, are achieving state-of-the-art performance in many graph mining tasks.
A Systematic Media Frame Analysis of 1.5 Million New York Times Articles from 2000 to 2017
By examining the ebb and flow of media frames over almost two decades, we show that short-term frame abundance fluctuation closely corresponds to major events, while there also exist several long-term trends, such as the gradually increasing prevalence of the ``Cultural identity'' frame.
FrameAxis: Characterizing Microframe Bias and Intensity with Word Embedding
{Here, we propose FrameAxis, a method for characterizing documents by identifying the most relevant semantic axes ("microframes") that are overrepresented in the text using word embedding.
Sameness Entices, but Novelty Enchants in Fanfiction Online
Cultural evolution is driven by how we choose what to consume and share with others.
SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment
Because word semantics can substantially change across communities and contexts, capturing domain-specific word semantics is an important challenge.
The Minor Fall, the Major Lift: Inferring Emotional Valence of Musical Chords through Lyrics
We investigate the association between musical chords and lyrics by analyzing a large dataset of user-contributed guitar tablatures.
Optimal modularity and memory capacity of neural reservoirs
The neural network is a powerful computing framework that has been exploited by biological evolution and by humans for solving diverse problems.
Element-centric clustering comparison unifies overlaps and hierarchy
Clustering is one of the most universal approaches for understanding complex data.
The Impact of Random Models on Clustering Similarity
It is often argued that, in order to establish a baseline, clustering similarity should be assessed in the context of a random ensemble of clusterings.
Gendered Conversation in a Social Game-Streaming Platform
Our findings suggest that disparities in social game-streaming platforms is a nuanced phenomenon that involves the gender of streamers as well as those who produce gendered and game-related conversation.
Information Overload in Group Communication: From Conversation to Cacophony in the Twitch Chat
Our analysis reveals the existence of a transition from a conversational state to a cacophony --- a state of overload with lower user participation, more copy-pasted messages, and less information per message.
Social and Information Networks Human-Computer Interaction Physics and Society
Link communities reveal multiscale complexity in networks
Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society.
Physics and Society Data Analysis, Statistics and Probability Quantitative Methods
