Build neural network models to identify and correct news headlines exaggerating obesity-related scientific findings

Purpose:Media exaggerations of health research may confuse readers’understanding,erode public trust in science and medicine,and cause disease mismanagement.This study built artificial intelligence(AI)models to automatically identify and correct news headlines exaggerating obesity-related research findings.Design/methodology/approach:We searched popular digital media outlets to collect 523 headlines exaggerating obesity-related research findings.The reasons for exaggerations include:inferring causality from observational studies,inferring human outcomes from animal research,inferring distant/end outcomes(e.g.,obesity)from immediate/intermediate outcomes(e.g.,calorie intake),and generalizing findings to the population from a subgroup or convenience sample.Each headline was paired with the title and abstract of the peer-reviewed journal publication covered by the news article.We drafted an exaggeration-free counterpart for each original headline and fined-tuned a BERT model to differentiate between them.We further fine-tuned three generative language models-BART,PEGASUS,and T5 to autogenerate exaggeration-free headlines based on a journal publication’s title and abstract.Model performance was evaluated using the ROUGE metrics by comparing model-generated headlines with journal publication titles.Findings:The fine-tuned BERT model achieved 92.5%accuracy in differentiating between exaggeration-free and original headlines.Baseline ROUGE scores averaged 0.311 for ROUGE-1,0.113 for ROUGE-2,0.253 for ROUGE-L,and 0.253 ROUGE-Lsum.PEGASUS,T5,and BART all outperformed the baseline.The best-performing BART model attained 0.447 for ROUGE-1,0.221 for ROUGE-2,0.402 for ROUGE-L,and 0.402 for ROUGE-Lsum.Originality/value:This study demonstrated the feasibility of leveraging AI to automatically identify and correct news headlines exaggerating obesity-related research findings.

A Study of Stylistic Features of English News Headlines

From different aspects we can draw out different characteristics of news headlines. According to various study and research from different authors, we can conclude their characteristics are displayed on syntactical level, punctuation level, lexical level, rhetorical level and cultural level.

An Analysis of English News Headlines

A headline is an indispensable component of a news report and is the eye of the pages on the newspapers,through which the readers can gain as much information as possible in the newspaper within the shortest time and search for clues to stories that interest them,as the headline is the condensation of the whole story.Despite their own characteristic ways of editing headlines,English newspapers share something in common,namely brevity,accuracy,clarity and eye-catchingness.However,these features unique to English newspaper headlines constitute a big barrier to readers' understanding of the headlines and they may become quite at loss when reading headlines at the very beginning.This thesis aims to make an analysis of English news headlines in terms of their features at structural,lexical and rhetorical levels and hopes to help readers understand English news headline better.

Features of English News Headlines

Nowadays Chinese people are attaching great importance to English news that not only offers worldwide information but gives a hand to English learners with their improvement in English.As is called the eyes of English news,headlines are partic ularly important.Generally speaking,English news headlines are precise,brief and as attractive as possible.They have their own grammar features and vocabulary features while different devices are employed to make them expressive and striking.

Translation of News Headlines Under Contextual Theory

With the coming of all kinds of information,the world is becoming one indivisible planet.People not only pay attention to major events in their own countries,but also gradually pay attention to international news and learn about the world situation.As one of the world’s common languages,English news accounts for a large proportion of the news market.Usually when people choose to read current events,they will look at the headlines first,and then at the content of the article.Therefore,whether the translated news headlines can accurately convey information and catch readers’attention in a short time plays a very important role in the dissemination of news.Based on the context theory,this paper studies and analyzes the translation of some news headlines,expecting to provide some suggestions for news translation.

An Analysis of Lexical Features of English News Headlines and Their Translation Skills

A headline is an inseparable component of news, which serves the role of eyes. So wring a brief, accurate and eye-catching headline is very important. With plenty of practical examples given, the paper discusses lexical features of English news headlines through different aspects, including the use of nouns and midget words, vogue words, derivatives, nonce words, loans and so on. It also introduces some translating strategies according to their distinctive lexical characteristics.

Study on Translation of English Financial News Headlines from the Perspective of Pragmatics

English financial news headlines are distinguished from other types of titles for its distinctive characteristics.Besidesthat,when it comes to the problem of different thinking modes,the core of the translation is to keep the pragmatic equivalence forthe sake of achieving effective communications in cross-cultural background.Based on analysis of the features of English financialnews headlines,this paper aims at searching for better translation strategies for these from the perspective of pragmatics.

Analysis on Features of News Headlines Translation

This paper is holding the purpose of summing up the theories and methods based on many examples which demonstrate principles,features and technique skills in news headline translation.We know that the translation of news headlines which is considered as the eyes and window of news appears very essential as many people do not have enough time to read the whole text from beginning to the end.They tend to browse headlines at first and then pick up the news in which the headline attracts them.From the paper,we can draw a conclusion that English news headline translation is not an easy task,and we need more study and practice to make it better and do our utmost to help Chinese readers when they are reading English newspapers or magazines.

A Study of Rhetorical Features of English News Headlines

As is known to all,headlines serve as a summary and advertisement for the main idea of the news so as to make the reader have a better understanding.Therefore,to some degree,we can say that the headline is the soul of a news report.Rhetoric,in all kinds of writing in all kinds of languages,can be applied and make an efficient effect.As for an English news headline,it is usually formed with certain rhetorical device to embody its soul and to appeal to more readers.This paper is to introduce and discuss the rhetorical features of the news headlines with examples and analysis.

A Study on the Ambiguity in English News Headlines from the Perspective of Cooperative Principle

In recent years,some news headlines do not focus on the contents of news,but exaggerate the fact.The main reason for this phenomenon is that the news editors disobey Cooperative Principle.As a result,it causes two different effects:one is negative;the other is positive.So the paper will find out the reasons of the ambiguity by using examples appearing in different newspapers and give a detailed analysis from the perspective of Cooperative Principle.

Theme-rheme Analysis of English News Headlines

As a special type of writing,news report has attracted more and more attention in different countries.Many people have developed an interest in reading English news,which provides them with timely information about important happenings around the world.Under the frame work of Systemic-Functional Grammar,based on English news headlines,the theme-rheme structure of English headlines is systemically analyzed in this thesis.Some detailed researches are made to investigate the influence of the Theme-rheme Structure in English news headlines.Then the news headline as well as its contents could be understood and enjoyed while reading newspaper.

On Zero Translation in News Discourse

In the context of globalization,zero translation words are more and more frequently used in news discourse.This article aims to explore the reasons for the frequent use of zero translation words in news discourse and their impact on news discourse from the perspectives of translation studies and journalism and communication studies.

Studyon the E-C Translation of Financial NewsHeadlines inthe Context of the Skopos Theory

As the heart of news,financial news headline determines whetherpeople are interested in the content.The purpose of translating financial news headlines is to accurately convey the financial information of foreign media to domestic readers and attract domestic readers’attention by means of rhetoric,typesetting,and so on.This paper mainly discusses how the Skopos Theory is applied in translating financial news headlines through case studies.In the context of Skopos Theory,translation principles for different financial news headlines will also be explored and summarized.

Roman Urdu News Headline Classification Empowered with Machine Learning

Roman Urdu has been used for text messaging over the Internet for years especially in Indo-Pak Subcontinent.Persons from the subcontinent may speak the same Urdu language but they might be using different scripts for writing.The communication using the Roman characters,which are used in the script of Urdu language on social media,is now considered the most typical standard of communication in an Indian landmass that makes it an expensive information supply.English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply of Roman Urdu in the past.This is due to the numerous complexities involved in the processing of Roman Urdu data.The complexities associated with Roman Urdu include the non-availability of the tagged corpus,lack of a set of rules,and lack of standardized spellings.A large amount of Roman Urdu news data is available on mainstream news websites and social media websites like Facebook,Twitter but meaningful information can only be extracted if data is in a structured format.We have developed a Roman Urdu news headline classifier,which will help to classify news into relevant categories on which further analysis and modeling can be done.The author of this research aims to develop the Roman Urdu news classifier,which will classify the news into five categories(health,business,technology,sports,international).First,we will develop the news dataset using scraping tools and then after preprocessing,we will compare the results of different machine learning algorithms like Logistic Regression(LR),Multinomial Naïve Bayes(MNB),Long short term memory(LSTM),and Convolutional Neural Network(CNN).After this,we will use a phonetic algorithm to control lexical variation and test news from different websites.The preliminary results suggest that a more accurate classification can be accomplished by monitoring noise inside data and by classifying the news.After applying above mentioned different machine learning algorithms,results have shown that Multinomial Naïve Bayes classifier is giving the best accuracy of 90.17%which is due to the noise lexical variation.

Chinese News Text Classification Based on Convolutional Neural Network

With the explosive growth of Internet text information,the task of text classification is more important.As a part of text classification,Chinese news text classification also plays an important role.In public security work,public opinion news classification is an important topic.Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time.This paper introduces a combinedconvolutional neural network text classification model based on word2vec and improved TF-IDF:firstly,the word vector is trained through word2vec model,then the weight of each word is calculated by using the improved TFIDF algorithm based on class frequency variance,and the word vector and weight are combined to construct the text vector representation.Finally,the combined-convolutional neural network is used to train and test the Thucnews data set.The results show that the classification effect of this model is better than the traditional Text-RNN model,the traditional Text-CNN model and word2vec-CNN model.The test accuracy is 97.56%,the accuracy rate is 97%,the recall rate is 97%,and the F1-score is 97%.

On Neologism in Broadcast News Reporting

Based on the neologism in the broadcast news reporting, this paper will introduce different kinds of the most frequently used words today, including the extended meanings of the conventional words and new words created by word formation.

WORD NEWS IN BRIEF(August 16-31, 1992)

Erazilians delivered a sharp rebuff on August 16 to President Fernando Collor de Mello, ignoring his plea to wear the national colours as opposition to the corruption charges threatening his government. Collor vigorously denied all the accusations against him. But thousands of demonstrators packed the streets of the country’s two biggest cities, Rio and Sao Paulo, calling for Collor’s impeachment and jailing.

WORD NEWS IN BRIEF

On July 16, US Texas billionaire Ross Perot abandoned his independent drive for the White House after concluding he "cannot win in November". Czechoslovak President Vaclav Havel resigned on July 20. He said his resignation should help clear the air in Czech and Slovakia, which are heading rapidly for a split.

WORD NEWS IN BRIEF(March 16-31, 1993)

Jiang Zemin, 67, was elected President of the People’s Republic of China on March 27 at the ongoing first, session of the Eighth National People’s Congress. He was also re-elected Chairman of the Central Military Commission of the country. Meanwhile, a non-Communist politician and a leading businessman, Rong Yiren, 77, was elected Vice-President. Qiao Shi, 69, was voted as Chairman of the Eighth National People’ Congress Standing Committee. Li Pemg’s re-appointment as Premier,

WORD NEWS IN BRIEF(March 1-15,1993)

Afghanistan eight main rival leaders, allies in Afghanistan’s 14-year insurgency, signed a peace accord on March 7 at the prime minister’s house in Islamabad after six days of intense negotiations. China and Tadzhikistan signed a joint declaration on March 9 in Beijing on the basic criteria governing their ties and 10 cooperation pacts ranging from mutual investment protection to China’s offer, of commodity