Results 41 to 50 of about 13,061 (196)

Analysis of the Structure of Scientific News Headlines in Online Newspapers

open access: yesمجلة كلية التربية للبنات, 2019
Newspaper headlines are described as compressed and ambiguous pieces of discourse that represent the bodies of the articles. Their main function is to provide the readers with an informative message they would have no prior idea about.
Lina Laith Younus
doaj   +1 more source

Learning to Flip the Bias of News Headlines [PDF]

open access: yesProceedings of the 11th International Conference on Natural Language Generation, 2018
This paper introduces the task of “flipping” the bias of news articles: Given an article with a political bias (left or right), generate an article with the same topic but opposite bias. To study this task, we create a corpus with bias-labeled articles from all-sides.com.
Wei-Fan Chen 0001   +3 more
openaire   +1 more source

Automatic Classification of Online News Headlines

open access: yes, 2007
The rise of online news over the past decade has altered how individuals obtain news and this study sought to determine the types of online news headlines most often selected by news websites as their "Top Stories". Headlines from four news websites were
Pope, Mark W.
core   +1 more source

The evolution of online news headlines

open access: yesHumanities and Social Sciences Communications
Abstract As the written word has moved online, new technological affordances and pressures – such as accelerated cycles of production and consumption – have changed how news headlines are produced and selected. Previous literature has linked certain strategies (e.g., clickbait) and linguistic features (e.g., length, negativity) to the success
Pietro Leonardo Nickl   +2 more
openaire   +2 more sources

Spoonerism in Primetime News headlines: an analysis of sound harmonization in Indonesian media

open access: yesCogent Social Sciences
A spoonerism is a linguistic phenomenon that involves switching sounds between two or more words. Spoonerism is frequently used in the headlines of news articles, where it is employed to maintain sound harmony and grab readers’ attention.
Muhardis
doaj   +1 more source

Fake News Detection with Headlines

open access: yes, 2023
Fake news has become an increasing problem due to the rising use of the Internet and social media. It is important to be able to distinguish sources of fake and misleading news articles to ensure that misinformation does not sow discord, erode trust in ...
Ramirez, Gared
core  

Factuality Checking in News Headlines with Eye Tracking

open access: yes, 2020
We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines. Our study with 55 participants who are eye-tracked when reading 108 news headlines (72 true, 36 false ...
Larsen, Birger; id_orcid   +12 more
core   +1 more source

A critical discourse analysis of narrative discrepancies in Pakistani news channel headlines

open access: yesCogent Arts & Humanities
This case study investigates how the same tweet is treated linguistically with different narratives. Taking the case of the tweet of Maryam Nawaz, a Pakistani female politician, we analyze through different linguistic interpretations the selected news ...
Awais Rubbani   +2 more
doaj   +1 more source

A computer-assisted textual analysis of 10,191 rape news headlines shared on social media

open access: yesSocial Sciences and Humanities Open, 2023
Although rape is prevalent in Bangladesh, we have limited knowledge about how the media reports rape news. This study analyzed 10,191 headlines of rape news shared on ten Bangladeshi media's Facebook pages between 2013 and 2021.
Md. Sayeed Al-Zaman
doaj   +1 more source

HeadlineCause: A Dataset of News Headlines for Detecting Causalities

open access: yesCoRR, 2021
Detecting implicit causal relations in texts is a task that requires both common sense and world knowledge. Existing datasets are focused either on commonsense causal reasoning or explicit causal relations. In this work, we present HeadlineCause, a dataset for detecting implicit causal relations between pairs of news headlines.
Ilya Gusev, Alexey Tikhonov
openaire   +3 more sources

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