Quote Erat Demonstrandum: A Web Interface for Exploring the Quotebank Corpus

• URL: http://arxiv.org/abs/2207.03592v1
• Date: Thu, 7 Jul 2022 21:41:03 GMT
• Title: Quote Erat Demonstrandum: A Web Interface for Exploring the Quotebank Corpus
• Abstract summary: We present an adaptive web interface for searching Quotebank, a massive collection of quotes from the news. Quotes play a central role in the conception, reception, and analysis of news stories.
• Score: 11.863216366085105
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The use of attributed quotes is the most direct and least filtered pathway of information propagation in news. Consequently, quotes play a central role in the conception, reception, and analysis of news stories. Since quotes provide a more direct window into a speaker's mind than regular reporting, they are a valuable resource for journalists and researchers alike. While substantial research efforts have been devoted to methods for the automated extraction of quotes from news and their attribution to speakers, few comprehensive corpora of attributed quotes from contemporary sources are available to the public. Here, we present an adaptive web interface for searching Quotebank, a massive collection of quotes from the news, which we make available at https://quotebank.dlab.tools.

Related papers

• Identifying Speakers in Dialogue Transcripts: A Text-based Approach Using Pretrained Language Models [83.7506131809624]
  We introduce an approach to identifying speaker names in dialogue transcripts, a crucial task for enhancing content accessibility and searchability in digital media archives. We present a novel, large-scale dataset derived from the MediaSum corpus, encompassing transcripts from a wide range of media sources. We propose novel transformer-based models tailored for SpeakerID, leveraging contextual cues within dialogues to accurately attribute speaker names.
  arXiv  Detail & Related papers  (2024-07-16T18:03:58Z)
• Tracking the Newsworthiness of Public Documents [107.12303391111014]
  This work focuses on news coverage of local public policy in the San Francisco Bay Area by the San Francisco Chronicle. First, we gather news articles, public policy documents and meeting recordings and link them using probabilistic relational modeling. Second, we define a new task: newsworthiness prediction, to predict if a policy item will get covered.
  arXiv  Detail & Related papers  (2023-11-16T10:05:26Z)
• Identifying Informational Sources in News Articles [109.70475599552523]
  We build the largest and widest-ranging annotated dataset of informational sources used in news writing. We introduce a novel task, source prediction, to study the compositionality of sources in news articles.
  arXiv  Detail & Related papers  (2023-05-24T08:56:35Z)
• Detecting Contextomized Quotes in News Headlines by Contrastive Learning [9.90130000354593]
  A direct quote enclosed in quotation marks has a strong visual appeal and is a sign of a reliable citation. Unfortunately, this journalistic practice is not strictly followed, and a quote in the headline is often "contextomized" Such a quote uses words out of context in a way that alters the speaker's intention so that there is no semantically matching quote in the body text. We present QuoteCSE, a contrastive learning framework that represents the embedding of news quotes based on domain-driven positive and negative samples.
  arXiv  Detail & Related papers  (2023-02-09T07:04:11Z)
• Multiverse: Multilingual Evidence for Fake News Detection [71.51905606492376]
  Multiverse is a new feature based on multilingual evidence that can be used for fake news detection. The hypothesis of the usage of cross-lingual evidence as a feature for fake news detection is confirmed.
  arXiv  Detail & Related papers  (2022-11-25T18:24:17Z)
• DIANES: A DEI Audit Toolkit for News Sources [7.864608835252345]
  We present DIANES, a DEI Audit Toolkit for News Sources. It consists of a natural language processing pipeline on the backend to extract quotes, speakers, titles, and organizations from news articles in real time.
  arXiv  Detail & Related papers  (2022-03-21T23:03:04Z)
• DirectQuote: A Dataset for Direct Quotation Extraction and Attribution in News Articles [6.006936459950188]
  This paper introduces DirectQuote, a corpus containing 19,760 paragraphs and 10,279 direct quotations manually annotated from online news media. For the first time, we propose several sequence labeling models as baseline methods to extract and attribute quotations simultaneously in an end-to-end manner.
  arXiv  Detail & Related papers  (2021-10-15T02:50:09Z)
• Context-Based Quotation Recommendation [60.93257124507105]
  We propose a novel context-aware quote recommendation system. It generates a ranked list of quotable paragraphs and spans of tokens from a given source document. We conduct experiments on a collection of speech transcripts and associated news articles.
  arXiv  Detail & Related papers  (2020-05-17T17:49:53Z)
• Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation [98.98411895250774]
  We propose generating multiple headlines with keyphrases of user interests. The proposed method achieves state-of-the-art results in terms of quality and diversity.
  arXiv  Detail & Related papers  (2020-04-08T08:30:05Z)
• BaitWatcher: A lightweight web interface for the detection of incongruent news headlines [27.29585619643952]
  BaitWatcher is a lightweight web interface that guides readers in estimating the likelihood of incongruence in news articles before clicking on the headlines. BaiittWatcher utilizes a hierarchical recurrent encoder that efficiently learns complex textual representations of a news headline and its associated body text.
  arXiv  Detail & Related papers  (2020-03-23T23:43:02Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.