1.2k citations · 1.2k across the 13 of their papers we have counts for
13 papers
Births are difficult to predict even with rich survey and full-population register data
Elizaveta Sivak, Emily M. Cantrell, Thomas Emery +109
Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child w…
A Methodological Guide on Using Large Language Models for Reproducible Text Annotation in the Social Sciences and Humanities with Python and R
Qixiang Fang, Javier Garcia Bernardo, Erik-Jan van Kesteren
Large language models (LLMs) are increasingly used by researchers in the social sciences and humanities (SSH) for text analysis, particularly to automate text annotation. However,…
PATCH! {P}sychometrics-{A}ssis{T}ed Ben{CH}marking of Large Language Models against Human Populations: A Case Study of Proficiency in 8th Grade Mathematics
Qixiang Fang, Daniel L. Oberski, Dong Nguyen
Many existing benchmarks of large (multimodal) language models (LLMs) focus on measuring LLMs' academic proficiency, often with also an interest in comparing model performance with…
USE: Dynamic User Modeling with Stateful Sequence Models
Zhihan Zhou, Qixiang Fang, Leonardo Neves +5
User embeddings play a crucial role in user engagement forecasting and personalized services. Recent advances in sequence modeling have sparked interest in learning user embeddings…
General-Purpose User Modeling with Behavioral Logs: A Snapchat Case Study
Qixiang Fang, Zhihan Zhou, Francesco Barbieri +6
Learning general-purpose user representations based on user behavioral logs is an increasingly popular user modeling approach. It benefits from easily available, privacy-friendly y…
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter +39
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…
Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions
Christian Fang, Qixiang Fang, Dong Nguyen
We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval). Because human values are subjective concepts which require p…
On Text-based Personality Computing: Challenges and Future Directions
Qixiang Fang, Anastasia Giachanou, Ayoub Bagheri +4
Text-based personality computing (TPC) has gained many research interests in NLP. In this paper, we describe 15 challenges that we consider deserving the attention of the research…
Improving Stance Detection by Leveraging Measurement Knowledge from Social Sciences: A Case Study of Dutch Political Tweets and Traditional Gender Role Division
Qixiang Fang, Anastasia Giachanou, Ayoub Bagheri
Stance detection concerns automatically determining the viewpoint (i.e., in favour of, against, or neutral) of a text's author towards a target. Stance detection has been applied t…
Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions
Qixiang Fang, Dong Nguyen, Daniel L Oberski
Text embedding models from Natural Language Processing can map text data (e.g. words, sentences, documents) to supposedly meaningful numerical representations (a.k.a. text embeddin…
Assessing the Reliability of Word Embedding Gender Bias Measures
Yupei Du, Qixiang Fang, Dong Nguyen
Various measures have been proposed to quantify human-like social biases in word embeddings. However, bias scores based on these measures can suffer from measurement error. One ind…
The Role of Time, Weather and Google Trends in Understanding and Predicting Web Survey Response
Qixiang Fang, Joep Burger, Ralph Meijers +1
In the literature about web survey methodology, significant efforts have been made to understand the role of time-invariant factors (e.g. gender, education and marital status) in (…
Open Source Software for Efficient and Transparent Reviews
Rens van de Schoot, Jonathan de Bruin, Raoul Schram +14
To help researchers conduct a systematic review or meta-analysis as efficiently and transparently as possible, we designed a tool (ASReview) to accelerate the step of screening tit…