Barriers and methodology in transitioning to sustainability: Analysing web news comments concerning animal-based diets

2021 ◽  
pp. 129857
Author(s):  
Katharine Heyl ◽  
Felix Ekardt
Keyword(s):  
2008 ◽  
Vol 1 (3) ◽  
pp. 273-285 ◽  
Author(s):  
Yair Galily

From its explosive development in the last decade of the 20th century, the World Wide Web has become an ideal medium for dedicated sports fanatics and a useful resource for casual fans, as well. Its accessibility, interactivity, speed, and multimedia content have triggered a fundamental change in the delivery of mediated sports, a change for which no one can yet predict the outcome (Real, 2006). This commentary sheds light on a process in which the talk-back mechanism, which enables readers to comment on Web-published articles, is (re)shaping the sport realm in Israeli media. The study on which this commentary is based involved the comparative analysis of over 3,000 talk-backs from the sports sections of 3 daily Web news sites (Ynet, nrg, and Walla!). The argument is made that talkbacks serve not only as an extension of the journalistic sphere but also as a new source of information and debate.


2013 ◽  
Vol 278-280 ◽  
pp. 2058-2064
Author(s):  
Cheng Ying Chi ◽  
Hong Li ◽  
Xue Gang Zhan ◽  
Sheng Nan Jiang

In this paper, through analysis of the structure of web news texts, we have proposed an improvement measure for term weighting in hot topics detection, and a topic weighting scheme for hot topics ranking. Experiment result comparison shows that our method is effective and ranking of hot topics is closer to reality.


Author(s):  
Mauricio Pandolfi-González ◽  
Christian Quesada-López ◽  
Alexandra Martínez ◽  
Marcelo Jenkins

2018 ◽  
Vol 9 ◽  
pp. 135-143
Author(s):  
Anna Hłuszko

Shock content as a manipulative component of conflict discourseDifficult socio-political situation in Ukraine creates specific media discourse, which in turn gives rise to a number of phenomena, connected to information war categories, war of meanings, hate speech etc. Active entry of military issues into web news content affects traditional approach to the media-text drafting. The report examines the trends of shock visual content and its announcement in the web headlines. The influence of the content emotionalization, which is one of the common features for conflict discourse, not only on text style, but also on features of page making, selection and use of photo illustrations, headline creation, is studied. The material covering military developments usually involve deaths, injuries, loss, destruction of settlements as a result of hostilities, that is, they focus on information on suffering of both military and civilians. This results in stronger integration of shock visual content into the news, which in turn may be used as manipulation and propaganda tool. On the one hand it is used to demonstrate crimes of the enemy, on the other — as an evidence of Ukrainian military success. From the point of view of ethic and humanism the justification of such tactic is doubtful in both cases. However, the study shows that open image of death, blood, injuries in the materials and the announcement of such content in headlines are the cause of high popularity of such publications, and this mainstreams the problem of dehumanizing impact both on material’s subjects and on media audience.


Author(s):  
Aye Nyein Mon ◽  
Win Pa Pa ◽  
Ye Kyaw Thu

This paper introduces a speech corpus which is developed for Myanmar Automatic Speech Recognition (ASR) research. Automatic Speech Recognition (ASR) research has been conducted by the researchers around the world to improve their language technologies. Speech corpora are important in developing the ASR and the creation of the corpora is necessary especially for low-resourced languages. Myanmar language can be regarded as a low-resourced language because of lack of pre-created resources for speech processing research. In this work, a speech corpus named UCSY-SC1 (University of Computer Studies Yangon - Speech Corpus1) is created for Myanmar ASR research. The corpus consists of two types of domain: news and daily conversations. The total size of the speech corpus is over 42 hrs. There are 25 hrs of web news and 17 hrs of conversational recorded data.<br />The corpus was collected from 177 females and 84 males for the news data and 42 females and 4 males for conversational domain. This corpus was used as training data for developing Myanmar ASR. Three different types of acoustic models  such as Gaussian Mixture Model (GMM) - Hidden Markov Model (HMM), Deep Neural Network (DNN), and Convolutional Neural Network (CNN) models were built and compared their results. Experiments were conducted on different data  sizes and evaluation is done by two test sets: TestSet1, web news and TestSet2, recorded conversational data. It showed that the performance of Myanmar ASRs using this corpus gave satisfiable results on both test sets. The Myanmar ASR  using this corpus leading to word error rates of 15.61% on TestSet1 and 24.43% on TestSet2.<br /><br />


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