• Journal of Scientific & Technological Knowledge Infrastructure
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• s.22
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• pp.8-9
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• 2006

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.14
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• pp.4-11
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• 2004

• Journal of The Korean Association For Science Education
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• v.14 no.3
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• pp.344-355
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• 1994

In this paper, science news in daily newspapers were reviewed to promote the reader's interest and the public science. The desirable direction in editing science columns was also suggested. For this, following studies were achieved. At first, terminologies used frequently in science columns of the Dong-A Daily News during six months (January 1993 - June), were collected and classified. Thr questionnaire were distributed to university students and general public, to analyze the public concern about the science news. Through the telephone interview with the editing staff of daily newspapers, current status and problems of science columns were investigated. As a result, the several conditions and recommendations are suggested, to promote science columns.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1365-1377
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• 2019

Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in the comparative analysis of news views between China and Vietnam. Aiming at cross-language problems in the analysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method of summarizing the differences based on an undirected graph model. The method extracts elements to represent the sentences, and builds a bridge between different languages based on Wikipedia's multilingual concept description page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, and filter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity grade as the weight of the edge to construct an undirected graph model. Finally, combining the random walk algorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highest weight can be extracted as the difference summary. The experiment results show that our proposed approach achieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-art summarization models.

• Korean journal of communication and information
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• v.32
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• pp.7-48
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• 2006

The study explores how Korea's major newspaper cover about science news, especially how newspaper frame biotechnology news including new source, news construction ways, coverage trend. The research has a research design to find out coverage pattern or model with frame theory. The result shows that the newspaper has some aspect of frame through out the biotechnology development in the section, theme, source, complexity. The section has been expend to the society and international section, while the theme shift from disease or cancer cure to life itself, genome, or stem cell. In the complexity, the biotechnology news stories have been developed a story plot (event-problem-development-solution). In the climax, the news coverage focuses on the explanation of biotechnology news.

• Journal of Korean Library and Information Science Society
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• v.44 no.3
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• pp.489-512
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• 2013

This study suggests the establishment and applications of the News core thesaurus for efficient indexing and searching of news information. News core thesaurus was constructed as macrothesauri which can cover all of news subjects and then has microthesauri like politics, economy, society, culture, etc. as its subsets. In this research, News core thesaurus embodied 2,012 descriptors and 74 non-descriptors by SKOS(Simple Knowledge Organization System). It suggests measures that treat only special subjects in detail in weekly newspaper or biweekly newspaper with little information and special subjects, which is not daily newspaper, and use each microthesauri by merging or integrating in huge news archives or portal sites.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.18-32
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• 2021

Social media has become a popular source of information around the world. Previous studies explored different trends of social media news consumption. However, no studies have focused on Bangladesh to date, where social media penetration is very high in recent years. To fill this gap, this research aimed to understand its popularity trends during the period. For that reason, this work analyzes 97.67 million page likes and 3.48 billion interaction data collected from nine Bangladeshi news media's Facebook pages between December 2016 to November 2020. The analysis shows that the growth rates of page likes and interaction rates declined during this period. It suggests that the media's Facebook pages are gradually losing their popularity among Facebook users, which may have two more interpretations: Facebook's aggregate appeal as a news source is decreasing to users, or Bangladeshi media's appeal is eroding to Facebook users. These findings challenge the previous results, i.e., Facebook's demand as a news source is increasing with time. We offer four explanations of the decreased popularity of Facebook's news: information overload, exposure to incidental news, users' selective exposure and different aims of using Facebook, and conflict between media agendas and users' interests. Some theoretical and practical significance of the results has been discussed as well.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.195-201
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• 2024

With the Covid-19(Corona Virus) spread all around the world, people are using this propaganda and the desperate need of the citizens to know the news about this mysterious virus by spreading fake news. Some Countries arrested people who spread fake news about this, and others made them pay a fine. And since Social Media has become a significant source of news, .there is a profound need to detect these fake news. The main aim of this research is to develop a web-based model using a combination of machine learning algorithms to detect fake news. The proposed model includes an advanced framework to identify tweets with fake news using Context Analysis; We assumed that Natural Language Processing(NLP) wouldn't be enough alone to make context analysis as Tweets are usually short and do not follow even the most straightforward syntactic rules, so we used Tweets Features as several retweets, several likes and tweet-length we also added statistical credibility analysis for Twitter users. The proposed algorithms are tested on four different benchmark datasets. And Finally, to get the best accuracy, we combined two of the best algorithms used SVM ( which is widely accepted as baseline classifier, especially with binary classification problems ) and Naive Base.

• The Science & Technology
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• s.511
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• pp.108-109
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• 2011

• The Science & Technology
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• s.544
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• pp.108-110
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• 2014