• Korean journal of communication and information
• /
• v.32
• /
• pp.7-48
• /
• 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 Information Technology Applications and Management
• /
• v.22 no.3
• /
• pp.19-33
• /
• 2015

SNS is perceived as an effective tool for sharing news and enabling news content to reach many more users than before. And some users think that SNS is an important source to get news. This study's purpose is to understand the key factors contributing to behavior of news consumption on social network sites in Cambodia and its influence. We identified three key factors including convenience, recency, and variety; however, recency showed less significant effect on news consumption on SNS. Besides the key factors, it also seeks to understand the impact of news consumption on social engagement and government's transparency in Cambodia. The analytical results achieved through the Partial Least Squares (PLS) approach.

• International Journal of Knowledge Content Development & Technology
• /
• v.11 no.4
• /
• pp.35-51
• /
• 2021

This study measured the effects of fake news and propaganda on managing information on COVID-19 among the Nigerian citizenry. This study examined sources of information on COVID-19 available to the people, evaluated reasons behind spreading fake news, examined how fake news has affected the spread of COVID-19 pandemic in Nigeria, established the consequences of fake news on managing COVID-19 pandemic and as well identified ways to contain fake news at a time like this in Nigeria.It is a survey with a sample size of 375 participants selected using simple random technique. Instrument of data gathering was questionnaire widely distributed in the six geo-political zones of Nigeria using Survey monkey. Data was analysed using frequencies, counts and percentages, tables and charts. Findings revealed that people rely more on radio, television, and social media for information on COVID-19. Fake news is spread by people mostly for political reasons and intention to cause panic. In Nigeria, fake news has led to disbelief of the existence of the virus thereby leading to violation of precautionary measures among the citizenry and lack of trust in the government. Concerted effort on the part of the government is required to give public enlightenment on the danger of fake news. Also, directorate of anti-fake news should be established to censor and reprimand sources of fake news. People should always check source of information to confirm its credibility and be weary of sharing unconfirmed information especially on the social media.

• International Journal of Computer Science & Network Security
• /
• v.21 no.2
• /
• pp.229-237
• /
• 2021

Our modern 'information-hungry' age demands delivery of information at unprecedented fast rates. Timely delivery of noteworthy information about recent events can help people from different segments of life in number of ways. As world has become global village, the flow of news in terms of volume and speed demands involvement of machines to help humans to handle the enormous data. News are presented to public in forms of video, audio, image and text. News text available on internet is a source of knowledge for billions of internet users. Urdu language is spoken and understood by millions of people from Indian subcontinent. Availability of online Urdu news enable this branch of humanity to improve their understandings of the world and make their decisions. This paper uses available online Urdu news data to train machines to automatically categorize provided news. Various machine learning algorithms were used on news headline for training purpose and the results demonstrate that Bernoulli Naïve Bayes (Bernoulli NB) and Multinomial Naïve Bayes (Multinomial NB) algorithm outperformed other algorithms in terms of all performance parameters. The maximum level of accuracy achieved for the dataset was 94.278% by multinomial NB classifier followed by Bernoulli NB classifier with accuracy of 94.274% when Urdu stop words were removed from dataset. The results suggest that short text of headlines of news can be used as an input for text categorization process.

• Journal of the Korean Home Economics Association
• /
• v.45 no.2
• /
• pp.105-117
• /
• 2007

The purpose of this study is to examine the producing conventions of lifestyle news and search for problems with these conventions. This research is about the entire process of production of lifestyle news, while dividing it into sourcing conventions and editing conventions. With this concept as a goal, we analyzed the content of lifestyle articles over the last six months in two types of daily papers, and then interviewed journalists in-depth. The results of the study indicate that as for sourcing conventions, reporting is accomplished by focusing on a reporter and using anonymous or false-named news sources. These conventions spread widely over not only ideas but also valuation of news items and security of news sources. This is because in terms of lifestyle news that is closely related to one's private life such as family relations, a reporter often attempts to prevent a news source from being exposed to secondary damage, such as the criticism of readers. In the meantime, editing conventions of lifestyle articles are irrelevant in terms of the quality of each media enterprise. Instead, these conventions are connected with the day of publication. Moreover, editors tend to approach editing conventions to spread the culture of upper classes, recognizing that the readers are consumers who have purchasing power.

• International Journal of Computer Science & Network Security
• /
• v.24 no.7
• /
• pp.195-201
• /
• 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 Journal of Society for e-Business Studies
• /
• v.23 no.4
• /
• pp.19-39
• /
• 2018

Recently, fake news has attracted worldwide attentions regardless of the fields. The Hyundai Research Institute estimated that the amount of fake news damage reached about 30.9 trillion won per year. The government is making efforts to develop artificial intelligence source technology to detect fake news such as holding "artificial intelligence R&D challenge" competition on the title of "searching for fake news." Fact checking services are also being provided in various private sector fields. Nevertheless, in academic fields, there are also many attempts have been conducted in detecting the fake news. Typically, there are different attempts in detecting fake news such as expert-based, collective intelligence-based, artificial intelligence-based, and semantic-based. However, the more accurate the fake news manipulation is, the more difficult it is to identify the authenticity of the news by analyzing the news itself. Furthermore, the accuracy of most fake news detection models tends to be overestimated. Therefore, in this study, we first propose a method to secure the fairness of false news detection model accuracy. Secondly, we propose a method to identify the authenticity of the news using the social data broadly generated by the reaction to the news as well as the contents of the news.

• Journal of Information Technology Applications and Management
• /
• v.25 no.1
• /
• pp.19-32
• /
• 2018

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

• Korean journal of communication and information
• /
• v.39
• /
• pp.140-177
• /
• 2007

The purposes of this study are to analyze how the media reflects the source competition between the activist group and the governmental source in the news contents. Media ideology and the conflict phase also were chosen as situational variables for evaluating how those variables could influence the source competition process. To answer the proposed research questions, the study chose the 'screen quota' issue as a research unit and analyzed documents from three sources, media news, the activist group for maintaining screen quota, and the governmental source during six years and three months. The results showed that the government source played a primary definer role in media reporting related to the screen quota issue, compared to the activist group. The governmental source's primary definer role was maintained against the highly contested social issue while the media ideology, to some degree, leveraged the activist group's comparatively unstable primary definer power. The governmental source's primary definer role was escalated as the conflict phase evolved.

• Korean journal of communication and information
• /
• v.81
• /
• pp.225-271
• /
• 2017

What is the basic nature of Korean public broadcasting system? This research explores this question through an analysis of KBS news coverage of the Korean housing market. This study spotlights the internal news production processes. In detail, this study investigates newsroom routines, such as news selection, news gatherings, and news production. As a result, this study reveals KBS can be classified as "Publicity Model" following reasons. First, KBS news selection process stresses higher viewer ratings for competitive market share and belittles public interests of serving the citizen. This caused KBS news to provide fragmented and truncated news information and to constrict high quality news of significant information for citizen. Second, KBS newsroom operates under the minimum staff resource to produce news programmes and has developed official source dependency as a routine for news gathering. Third, under the limits of report format, KBS news worked as a neutral deliverer of government message and failed to provide more detailed information and diverse viewpoints.