Evaluation of Thematic Coherence in Microblogs
Iman Munire Bilal, Bo Wang, Maria Liakata, Rob Procter, Adam Tsakalidis
Abstract
Collecting together microblogs representing opinions about the same topics within the same timeframe is useful to a number of different tasks and practitioners. A major question is how to evaluate the quality of such thematic clusters. Here we create a corpus of microblog clusters from three different domains and time windows and define the task of evaluating thematic coherence. We provide annotation guidelines and human annotations of thematic coherence by journalist experts. We subsequently investigate the efficacy of different automated evaluation metrics for the task. We consider a range of metrics including surface level metrics, ones for topic model coherence and text generation metrics (TGMs). While surface level metrics perform well, outperforming topic coherence metrics, they are not as consistent as TGMs. TGMs are more reliable than all other metrics considered for capturing thematic coherence in microblog clusters due to being less sensitive to the effect of time windows.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 3415b6e6-bb7b-4748-9719-0c8f4bae0758Cited by top-tier papers1
Ask how each one uses itBuilds on3
- BERTScore: Evaluating Text Generation with BERTTianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger et al.ICLR 2020 · 8,443 citations
- Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling DecoderXiaobao Wu, Chunping Li, Yan Zhu, Yishu MiaoEMNLP 2020 · 61 citations
- BLEURT: Learning Robust Metrics for Text GenerationThibault Sellam, Dipanjan Das, Ankur P. ParikhACL 2020 · 40 citations
Related papers
- Large-Scale Correlation Analysis of Automated Metrics for Topic ModelsJia Peng Lim, Hady W. LauwACL 2023 · 13 citations
- Is Automated Topic Model Evaluation Broken? The Incoherence of CoherenceAlexander Miserlis Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov et al.NeurIPS 2021 · 220 citations
- Evaluating Dynamic Topic ModelsCharu James, Mayank Nagda, Nooshin Haji Ghassemi, Marius Kloft et al.ACL 2024 · 1 citation
- ProxAnn: Use-Oriented Evaluations of Topic Models and Document ClusteringAlexander Miserlis Hoyle, Lorena Calvo-Bartolomé, Jordan Lee Boyd-Graber, Philip ResnikACL 2025
- Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text SpatializationDaniel Atzberger, Tim Cech, Matthias Trapp, Rico Richter et al.IEEE VIS 2023 · 11 citations
