• Title/Summary/Keyword: Online Social Decision

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How Content Affects Clicks: A Dynamic Model of Online Content Consumption

  • Inyoung Chae;Da Young Kim
    • Asia pacific journal of information systems
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    • v.31 no.4
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    • pp.606-632
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    • 2021
  • With many consumers being exposed to news via social media platforms, news organizations are challenged to attract visitors and generate revenue during visits to their websites. They therefore need detailed information on how to write articles and headlines to increase visitors' engagement with the content to drive advertising revenues. For those news organizations whose business model depends mainly on advertisements, rather than subscriptions, it is particularly crucial to understand what makes the website attractive to their visitors, what drives users to stay on the website, and what factors affect a user's exit decision. The current research examines individual news consumers' choices to find patterns of increase or decrease in user engagement relative to a variety of topics, as well as to the mood or tone of the content. Using clickstream data from a major news organization, the authors develop a user-level dynamic model of clickstream behavior that takes into account the content of both headlines and stories that visitors read. The authors find that readers appear to exhibit state dependence in the tone of the articles that they read. They also show how the topics expressed in headlines can affect the amount of content readers consume when visiting the news organization to a much larger degree than the topics expressed in the content of the article. Online publishers can make use of such findings to present visitors with content that is likely to maintain and/or increase their engagement and consequently drive advertising revenue.

Data Analysis of Facebook Insights (페이스북 인사이트 데이터 분석)

  • Cha, Young Jun;Lee, Hak Jun;Jung, Yong Gyu
    • The Journal of the Convergence on Culture Technology
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    • v.2 no.1
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    • pp.93-98
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    • 2016
  • As information technologies are rapidly developed recently, social networking services through a variety of mobile devices and smart screen is becoming popular. SNS is a social networking based services which is online forms from existed offline. SNS can also be used differently which is confused with the online community. A modelling algorithm is a variety of techniques, which are assocoation, clustering, neural networks, and decision trees, etc. By utilizing this technique, it is necessary to study to effectively using the large number of materials. In this paper, we evaluate in particular the performance of the algorithm based on the results of the clustering using Facebook Insights data for the EM algorithm to be evaluated as a good performance in clustering. Through this analysis it was based on the results of the application of the experimental data of the change and the South Australian state library according to the performance of the EM algorithm.

Sentiment Analysis of Product Reviews to Identify Deceptive Rating Information in Social Media: A SentiDeceptive Approach

  • Marwat, M. Irfan;Khan, Javed Ali;Alshehri, Dr. Mohammad Dahman;Ali, Muhammad Asghar;Hizbullah;Ali, Haider;Assam, Muhammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.830-860
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    • 2022
  • [Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

Consumers' acceptance and resistance to virtual bank: views of non-users (인터넷전문은행 수용 의도와 저항에 관한 연구: 소비자, 혁신, 환경 특성을 중심으로)

  • Kim, Hyo Jung;Lee, Seung Sin
    • Human Ecology Research
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    • v.57 no.2
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    • pp.171-183
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    • 2019
  • Convergence between technology and financial services is ubiquitous and widespread. Virtual banks represent an important aspect of financial markets that can generate value added for consumers and enhance the quality of financial services. This study explores the effect of innovation characteristics (relative advantage, compatibility, and perceived risk), consumer characteristics (status quo bias), and social mechanisms (network externality: complementarity, numbers of peers) on consumers' adoption intention and resistance to virtual banks. This study adopted an innovation resistance model with two dependent variables: adoption intention and resistance to virtual banks. An online self-administered survey was conducted and 532 or non-users of virtual banks aged 20 to 69 years old were analyzed. Frequency analysis, descriptive analysis, and hierarchical multiple regression indicated that status quo bias, relative advantage, perceived risk, complementarity, and number of peers insignificantly influence the adoption intention regarding virtual banks. Furthermore, status quo bias, relative advantage, perceived risk, and number of peers insignificantly influence the resistance to virtual banks. Female respondents have a lower adoption intention and higher resistance to virtual banks than male respondents. The findings suggest that the innovation resistance model can be useful in understanding consumers'adoption and resistance behavior as well as reveal that innovation characteristics, consumer characteristics, and social mechanism are important antecedent variables of the innovation adoption decision.

A Study on the Impact of Perceived Value of Art Based on Artificial Intelligence on Consumers' Purchase Intention

  • Wang, Ruomu
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.275-281
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    • 2021
  • The purpose of this research is to explore what factors affect consumers' purchasing decisions when purchasing artificial intelligence artworks. The research pointed out that in the real shopping model, customer perceived value includes three dimensions: product perceived value, service perceived value and social perceived value. On this basis, an artificial intelligence work purchase decision-making influence model was constructed, and an online survey was attempted to collect data. Through analysis of the reliability, effectiveness and structural equations of SPSS24.0 and AMOS24.0, and scientific verification and analysis, we found that product cognitive value and service cognitive value have a positive impact on consumers' purchase intentions, but social cognition Value has no positive effect on consumers' purchasing intentions.

Leadership Experience through Guild Activities on Online Games : A Phenomenological Analysis (온라인 게임의 길드 활동을 통한 리더십 경험 : 현상학적 분석)

  • Kim, Ki-Suk;Jung, Hyung-Won
    • Journal of Digital Convergence
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    • v.14 no.6
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    • pp.415-423
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    • 2016
  • Numerous studies have been made on the negative effects of online games, as the negatives effects of the usage of online games have been recognized as social issues. However, this is a study on the positive functions of online gaming; more specifically, on how the guild activities on online games affect the user's leadership. This study has conducted in-depth interviews with online games, and drew the result using Giorgi's phenomenological analysis as for the methodology. 3 people participated in the research - a high school student, a university student, and an adult office worker - all of whom with experiences of guild leading on online games. To achieve the goal of this study, this study based the subjects' experience to analyze how online game guild activities have affected leadership on the subjects' real lives. As a result, timidity turned into initiation; not only leadership, but also decision making ability and coworking ability, as well as problem solving ability have shown improvement. Through this study, one can see that among the elements of online game, experience in guild activities is providing opportunities for enhancing leadership and possibilities for improving various other abilities. I hope more researchers continue studying interesting and diverse powers of online games based on this study.

Geographical Characteristics and Patients' Determinants of Online Referrals : A Case Study of Choongbook, Korea (온라인 협진에 대한 지리적 특성과 환자의 결정에 관한 연구 : 충청북도 사례를 중심으로)

  • Park, Soo-Kyung
    • Journal of the Korean association of regional geographers
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    • v.17 no.5
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    • pp.617-637
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    • 2011
  • This study employs qualitative approaches to examining geographical characteristics and patients' determinants of online referrals in terms of regionalization. In this light, I conducted interviews with 20 patients receiving online referrals in Choongbook, Korea, and investigated their behaviors regarding these referrals between July and August 2009. I found that many patients who suffered from various levels of illness preferred tertiary care centers outside of Choongbook and did not enjoy their experience with the local medical institutions as the online referral service sites. This result might be because patients choose online referrals for psychological considerations such as quality and level of health care services, personal stakes in online referral service sites, acceptability and credibility of good tertiary care centers, and easy access to and use of medical institutions. Meanwhile, immediate benefits with regard to the technological value of online referrals, such as convenience, utility, and original purpose associated with regionalization, did not influence patients' decision-making. Therefore, the social and public networks affiliated with online referrals plus the effect of Korean medical laws play hostage to private decisions made by citizens, who prefer high-level medical institutions. Accordingly, the technological contribution of online referrals does not halt the outflow of patients from local, tertiary care centers. Especially, the existing health care system and patients' behaviors are deeply related to referrals in the online system. To protect regionalization, the improvement of health care services from the present state of affairs is required.

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Korean Customer Attitudes Towards SNS Shopping

  • Cho, Young-Sang;Heo, Jeong-Yoon;Youn, Myoung-Kil
    • Journal of Distribution Science
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    • v.10 no.8
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    • pp.7-14
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    • 2012
  • As a new format of retailing, social shopping on SNS has rapidly grown in recent. Although there is much literature associated with customer behaviours in the academic world, little attention has been paid to identifying the shopping patterns of SNS shoppers. This paper will, thus, identify how perceived value has an impact on the buying intention of SNS shoppers, after illustrating what kind of factor influences the formation process of perceived value in the Korean marketplace. Given that SNS shoppers are for the most part 20s as well as 30s, the authors handed out questionnaires to them. Furthermore, based on literature review results, the conceptualised research model was developed. Despite lack of literature, the authors developed five constructs like price reduction, quantity- and time-limited message, product ranges, information-sharing, and required number of shoppers. The researchers made a considerable effort to identify the relationship between research concepts and each variable, based on a few research analysis methods such as frequency analysis, the Varimax rotation technique used orthogonal rotation, Cronbach's Alpha, PCA (Principle Component Analysis), and the like. Amongst the 5 variables used to measure the degree of influences on the perceived value as a social shopping characteristic, it has been evident that price cut, required minimum shoppers, product variety, and information-sharing have a positive impact on the perceived value formation processes of SNS customers. Also, this research implies that SNS retailers can differentiate themselves from other retailers by differently using the above factors. From a practitioner's point of view, these factors should be strategically used to increase the social shopping opportunities of SNS users. It is, furthermore, evident that the perceived value formed by the above 4 factors have played an important role in the buying decision process of SNS customers. In a sense, whether customers are aware of higher price cut rates, information-sharing, required minimum shoppers, and product variety has a positive impact on making buying decisions. From a retailer's point of view, online shopping mall operators are able to use blog as well as twitter to improve the buying intention as a marketing tool of social network, because the business activities provided by social shopping retailers, like the rapid, accurate responses to customer requirements, the provision of a variety of information, and the communications between customers are closely related to buying intentions. There are a few research limitations to conduct this empirical research. It was not easy to review prior papers, due to its lack. In spite of the increasing number of SNS shoppers in Korea, little research attention has been paid to this kind of research topic by academicians, because buying products or services through SNS is in its infancy. With regard to research populations, it would be difficult to generalise the research findings in Korea, owing to unbalanced respondent distribution. Considering the above research limitations as well as the growth of social shopping, many authors should pay considerable attention to SNS-related issues in the future, and develop the more sophisticated criteria to measure the characteristics of SNS shoppers.

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Who Can be the Target of SNS Review Marketing? : A Study on the SNS Based Marketing Strategy (SNS 구매후기는 누구의 마음을 움직이는가? : 소셜 네트워크 서비스를 활용한 마케팅 전략 연구)

  • Shim, Seonyoung
    • Journal of Information Technology Services
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    • v.11 no.3
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    • pp.103-127
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    • 2012
  • With the advent of SNS (Social Network Services), the product reviews by friends in SNS are intensively utilized for online marketing. However, there is a lack of empirical evidence on the actual marketing effect of SNS reviews, although we need to identify who can be the target of SNS marketing in terms of customer attributes, preferences, or experiences. In this study, we investigate the moderating role of customer attributes in identifying the effect of SNS reviews on customer purchasing decision. As the moderating variables, we adopt 'information search experience' and 'perception of information overload'. Research results evidence that, in order to understand the effect of SNS reviews in a comprehensive manner, we need to examine it in the context of various related factors such as 'information search experience' and 'perception of information overload'. The results show that the persuading effect of SNS reviews for product purchasing is stronger for the customers with the lower information search experiences as well as the lower perception on the information overload on the web. This result delivers managerial implications on who can be the target customers of SNS marketing.

Analyzing Online Fake Business News Communication and the Influence on Stock Price: A Real Case in Taiwan

  • Wang, Chih-Chien;Chiang, Cheng-Yu
    • Journal of Information Technology Applications and Management
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    • v.26 no.6
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    • pp.1-12
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    • 2019
  • On the Internet age, the news is generated and distributed not only by traditional news media, but also by a variety of online news media, news platforms, content websites/content farms, and social media. Since it is an easy task to create and distribute news, some of these news reports may contain fake or false facts. In the end, the cyberspace is full of fake or false messages. People may wonder if these fake news actually influence our decision making. In this paper, we discussed a real case of fake news. In this case, a Taiwanese company used some fake news, advertorial news, and news placement to manipulate or influence its stock price and trade volume. We collected all news for the case company during a period of four years and five months (from January 2013 to May 2017). We analyzed the relationship between published news and stock price. Based on the analysis results, we conclude that we should not ignore the influence of news placement and fake business news on the stock price.