相关论文: Exploring Xenophobic Events through GDELT Data Ana…

Within the field of media framing, homelessness has been a historically under-researched topic. Framing theory states that the media's method of presenting information plays a pivotal role in controlling public sentiment toward a topic. The…

Holistic analysis of many real-world problems are based on data collected from multiple sources contributing to some aspect of that problem. The word fusion has also been used in the literature for such problems involving disparate data…

We aim to develop a tool for understanding how the mental health of youth aged less than 18 years evolve over time through administrative records of mental health related emergency department (MHED) visits in two decades. Administrative…

This study applies Natural Language Processing techniques, including Latent Dirichlet Allocation, to analyse anonymised maternity incident investigation reports from the Healthcare Safety Investigation Branch. The reports underwent…

Nowadays social media platforms such as Twitter provide a great opportunity to understand public opinion of climate change compared to traditional survey methods. In this paper, we constructed a massive climate change Twitter dataset and…

This extended abstract describes an ongoing project that attempts to blend publicly available organic, real time behavioral data, event data, and traditional migration data to determine when and where people will move during times of…

T\"urkiye is located on a fault line; earthquakes often occur on a large and small scale. There is a need for effective solutions for gathering current information during disasters. We can use social media to get insight into public…

The progress of event extraction research has been hindered by the absence of wide-coverage, large-scale datasets. To make event extraction systems more accessible, we build a general-purpose event detection dataset GLEN, which covers 205K…

Babel Briefings is a novel dataset featuring 4.7 million news headlines from August 2020 to November 2021, across 30 languages and 54 locations worldwide with English translations of all articles included. Designed for natural language…

The task of identifying public opinions on social media, particularly regarding climate activism and the detection of hate events, has emerged as a critical area of research in our rapidly changing world. With a growing number of people…

We report on an ethnographic study with members of the climate movement in the United Kingdom (UK). We conducted participant observation and interviews at protests and in various activist settings. Reporting on the findings as they relate…

This paper explores digital privacy challenges for migrants, analyzing trends from 2013 to 2023. Migrants face heightened risks such as government surveillance and identity theft. Understanding these threats is vital for raising awareness…

Sentiment analysis is the process of identifying and extracting subjective information from text. Despite the advances to employ cross-lingual approaches in an automatic way, the implementation and evaluation of sentiment analysis systems…

Between January 2017 and January 2021, thousands of local news sources in the United States reported on over 42,000 protests about topics such as civil rights, immigration, guns, and the environment. Given the vast number of local…

With an increasing amount of information on globally important events, there is a growing demand for efficient analytics of multilingual event-centric information. Such analytics is particularly challenging due to the large amount of…

Generative document retrieval, an emerging paradigm in information retrieval, learns to build connections between documents and identifiers within a single model, garnering significant attention. However, there are still two challenges: (1)…

This study examines cross-cultural interactions between Chinese users and self-identified "TikTok Refugees"(foreign users who migrated to RedNote after TikTok's U.S. ban). Based on a dataset of 1,862 posts and 403,054 comments, we use large…

In this paper, we present a dataset of 713k articles collected between 02/2018-11/2018. These articles are collected directly from 194 news and media outlets including mainstream, hyper-partisan, and conspiracy sources. We incorporate…

We present a dataset of video descriptions, comments, and user statistics, from the social media platform TikTok, centred around the invasion of Ukraine in 2022, an event that launched TikTok into the geopolitical arena. User activity on…

Our study addresses a significant gap in online hate speech detection research by focusing on homophobia, an area often neglected in sentiment analysis research. Utilising advanced sentiment analysis models, particularly BERT, and…