3 Linking Online News and Social Media

The Media Bias Detector: A framework for annotating and analyzing the news

The Media Bias Detector is introduced, a scalable computational framework that integrates large language models (LLMs) with near-real-time news scraping to extract structured annotations, including political lean, tone, topics, article type, and major events, across hundreds of articles per day.

From Web(logs) to Web(AI): Questions, Platforms, and Methods across Twenty Editions of ICWSM

Over twenty editions, the ICWSM community has examined social life online as platforms, interactions, and research methods have changed. What can this body of research tell us at this critical juncture, as AI increasingly reshapes how people communicate online? We analyzed 2,139 indexed contributions from 2007 to 2026,...

Topic Modeling and Sentiment Analysis on News Headlines Using BERTopic and IndoBERT Models

The findings confirm that the combination of transformer-based models is effective for in-depth analysis of discourse in Indonesian-language political news headlines from a major Indonesian online news portal (detik.com).

CHAT WITH YOUR PDF - MULTI DOCUMENT Q&A WITH SOURCE CITATIONS

The Chat with Your PDF — Multi-Document Q&A with Source Citations system is an intelligent document-question-answering platform that allows users to interact with multiple PDF documents using natural language. Users often need to read large documents such as research papers, textbooks, reports, manuals, policies, and b...

Linking on the Topology of Entity Co-occurrence Networks for Social Media Analysis

This work constructs multiple entity co-occurrence networks using two tools (Fast Entity Linker and DBpedia Spotlight) and numerous confidence thresholds for each and proves that standard network analysis metrics, such as size, connectivity, and centrality are all heavily influenced by the choice of entity linking tool.

A multi-view graph learning approach with RoBERTa for Twitter sentiment analysis