• International Journal of Contents
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• v.12 no.3
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• pp.1-11
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• 2016

This exploratory study examines the critical factors associated with news consumers' perception of information overload and news consumption patterns. An online survey was conducted with Qualtrics panels (N = 1001). The demographics and three antecedent factors of perceived information overload were considered including the frequency of news access through multiple media platforms, level of attention to news, and interest in news. Three news consumption patterns were investigated as possible consequences of perceived information overload: news avoidance, selective exposure, and willingness to pay for news. The results of hierarchical regression analyses revealed a meaningful distinction between general and news information overload. Overall, news consumers who paid more attention to news through newer media/platforms/devices perceived higher levels of information overload, were more willing to pay for the news, and often avoided news or selectively exposed themselves to certain sources of news to manage news information overload.

• Information Systems Review
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• v.25 no.3
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• pp.1-26
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• 2023

A theoretical model of information overload (Jackson and Farzaneh, 2012) with its three influential components (i.e., time, technology, and social networks) was empirically tested in the context of news consumption behavior considered as a communicative outcome. Using a national sample of South Korean adults (N = 1166), data analyses identified perceived information overload and large/diverse social networks positively associated with active and passive news consumption. Findings may imply the existence of individually varying cognitive threshold (i.e., tipping point), if crossed individuals cannot process information any further. News consumers may keep searching and receiving information to verify factuality of news even when they feel overloaded.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.31-42
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• 2024

Today, news avoidance has become an inevitable trend, particularly exacerbated since the outbreak of the COVID-19 pandemic in 2020. To delve deeper into the shifting tendencies of news consumers towards news avoidance and unveil the motivations behind this avoidance, this study recruited 500 Chinese news consumers aged between 20 and 60 years old, employing survey questionnaires as the research method. Through an indepth examination of their news consumption behavior at different stages of the COVID-19 pandemic, we discovered that individuals' risk perceptions and efficacy beliefs significantly influence their patterns of news consumption. Furthermore, we identified negative emotions, information overload, and media distrust as the primary reasons for news avoidance among Chinese news consumers during the COVID-19 crisis. These findings Not only provide crucial insights into understanding the dynamics of news consumption behavior but also offer valuable reference points for the news industry to better fulfill its role and value during crises in the future.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• 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.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.22-30
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• 2021

Objectives: The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency posing unprecedented challenges for health authorities. Social media may serve as an effective platform to disseminate health-related information. This study aimed to assess the extent of social media use, its impact on preventive behavior, and negative health effects such as cyberchondria and information overload. Methods: A cross-sectional observational study was conducted between June 10, 2020 and August 9, 2020 among people visiting the outpatient department of the authors' institution, and participants were also recruited during field visits for an awareness drive. Questions were developed on preventive behavior, and the Short Cyberchondria Scale and instruments dealing with information overload and perceived vulnerability were used. Results: The study recruited 767 participants with a mean age of about 45 years. Most of the participants (>90%) engaged in preventive behaviors, which were influenced by the extent of information received through social media platforms (β=3.297; p<0.001) and awareness of infection when a family member tested positive (β=29.082; p<0.001) or a neighbor tested positive (β=27.964; p<0.001). The majority (63.0%) of individuals often searched for COVID-19 related news on social media platforms. The mean±standard deviation scores for cyberchondria and information overload were 9.09±4.05 and 8.69±2.56, respectively. Significant and moderately strong correlations were found between cyberchondria, information overload, and perceived vulnerability to COVID-19. Conclusions: This study provides evidence that the use of social media as an information- seeking platform altered preventive behavior. However, excessive and misleading information resulted in cyberchondria and information overload.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.1
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• pp.64-75
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• 2024

With the development of the Internet, the information in our lives has become fast and diverse. Especially in the field of defense, articles and information are pouring in from various sources every day, and fast information selection, understanding, and decision-making are required in the ever-changing situation. It is very cumbersome to go from platform to platform and read articles one by one to get the information you need. To solve this problem, this research aims to save time and provide quick access to the latest information by allowing you to quickly grasp key information from summarized content without having to read the entire article. This can improve efficiency by allowing defense professionals to focus more on important tasks rather than extensive information search and analysis.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.211-226
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• 2016

Most of the SNS users argue that they feel techno-stress or digital fatigue when they use SNS. As the relationships in the SNS expand, users may feel work overload, digital fatigue, and techno-stress which are caused by the time and effort for the retaining the existing relationships established via SNS. The SNS activities require users' time and effort to update their profiles and the current news of them, responding to online friends' contents. Thus, more relationships they have, more stress they can feel. This study tries to examine the key factors that can affect subjective well-being of individuals in Social Network Service (SNS) usage. Therefore, this study, based on the previous literature, investigates what the sources of SNS stress are and how SNS stress and flow affect subjective well-being of SNS users. Major findings of this study from an empirical analysis with 201 SNS user respondents who have accessed SNS at least one time within one month are as follows. First, perceived opportunity cost and reputation recognition in SNS usage were found to have significant effects on negative emotion. Second, individual's flow in SNS was significantly affected by challenges and interactions, and had a significant impact on positive emotion. However, SNS users' flow did not show a positive relationship with their satisfaction of life. This study contributes to the expansion of theoretical discussion about the effect of individual's SNS usage on quality of life in validating whether SNS usage can bring individuals subjective well-being. Implications of the study findings and future research directions are also discussed.

• Information Systems Review
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• v.17 no.2
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• pp.219-238
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• 2015

As Internet and IT have been developed, people have been exposed to large amounts of information. So, many online information providers recommend relevant information to users to relieve an information overload. However, information recommendation which is based on the taste and preference of a user can lead to a problem of unbalanced information consumption. Prior research about online information has not investigated the side-effect of a recommendation function. This research suggests IT solutions for alleviating unbalanced information consumption behavior. Based on adaptation level theory and expectancy theory, we proposed self-reference point diagnosticity interface and social-reference point diagnosticity interface to help people to consume information following their own information consuming goal. We hypothesized positive impacts of these two interfaces on the self-awareness about information consuming pattern. And we predicted that self-awareness has a positive impact on the motivation and actual behavior to conform the ideal information consuming pattern which the user sets. Laboratory experiment was executed as a research method. As a result, the self-reference diagnosticity interface leaded to higher self-awareness and mitigated the unbalanced information consumption. But, the social-reference diagnosticity interface and the motivation to improve the information consuming behavior had no significant results. Academic and practical implications are discussed.