• Title/Summary/Keyword: User-Generated Information

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A Study on User-Generated Metadata (이용자 생성 메타데이터에 관한 연구)

  • Lee, Jae-Yun;Hwang, Hye-Kyong
    • Journal of Information Management
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    • v.37 no.3
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    • pp.1-24
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    • 2006
  • As the amount of information through growing Internet has dramatically increased recently, information professions generated metadata has been reached the limits of their role. Based on the value of information depends on the user, user generated metadata is a growing paradigm in the field of information organization today. This paper firstly introduces the concepts of user-generted metadata, and then examines the cases of user annotation and user tagging. Finally we discuss the effects and implications of user-generated metadata on the development of digital libraries.

Trust in User-Generated Information on Social Media during Crises: An Elaboration Likelihood Perspective

  • Pee, L.G.;Lee, Jung
    • Asia pacific journal of information systems
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    • v.26 no.1
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    • pp.1-21
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    • 2016
  • Social media is increasingly being used as a source of information during crises, such as natural disasters and civil unrests. However, the quality and truthfulness of user-generated information on social media have been a cause of concern. Many users find distinguishing between true and false information on social media difficult. Basing on the elaboration likelihood model and the motivation, opportunity, and ability framework, this study proposes and empirically tests a model that identifies the information processing routes through which users develop trust, as well as the factors that influence the use of these routes. The findings from a survey of Twitter users seeking information about the Fukushima Daiichi nuclear crisis indicate that individuals evaluate information quality more when the crisis information has strong personal relevance or when individuals have low anxiety about the crisis. By contrast, they rely on majority influence more when the crisis information has less personal relevance or when these individuals have high anxiety about the crisis. Prior knowledge does not have significant moderating effects on the use of information quality and majority influence in forming trust. This study extends the theorization of trust in user-generated information by focusing on the process through which users form trust. The findings also highlight the need to alleviate anxiety and manage non-victims in controlling the spread of false information on social media during crises.

An NLP-based Mixed-method Approach to Explore the Impact of Gratifications and Emotions on the Acceptance of Amazon Go

  • Arghya Ray;Subhadeep Jana;Nripendra P. Rana
    • Asia pacific journal of information systems
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    • v.33 no.3
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    • pp.541-572
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    • 2023
  • Amazon Go is a cashierless convenience store concept, which is seen as a disruption in the grocery retail segment. Although Amazon Go has the ability to disrupt the retail segment, there are speculations on how Amazon Go will be perceived by users. Existing studies have not utilized user-generated content to understand the factors that affect customer behaviour in case of Amazon Go. Additionally, in case of phygital retail, studies have not attempted at understanding the effect of emotions and gratifications on user behaviour. To address the gap of exploring user perspectives based on their experience, we have examined the impact of gratifications and emotions on the acceptance of phygital retail using user-generated-content. A mixed-method approach has been utilized using only user-generated content. Utilizing topic-modelling based content analysis and emotion analysis on 30 articles related to Amazon Go, we found themes like, convenience, technology, experience, personalization, enjoyment and emotions like, bad, good, annoyance, success. In the empirical analysis, we have utilized 522 reviews about Amazon Go from the cognition and emotion theory stance, and found that hedonic gratifications have a positive impact on challenge emotions. We also found a significant impact of emotions on customer's favourite behaviour.

Witty or wicked? The predictors and impact of agreement with user-generated political satires

  • Chen, Chi-Ying;Chang, Shao-Liang
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.3
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    • pp.25-30
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    • 2016
  • User-generated content (UGC) satirizing the presidential candidates was widespread during the 2016 election in Taiwan. Using an experimental design, this study explored the predictors of viewer agreement to satirical UGC, and its influence on viewer attitudes towards candidates after watching the satirical videos from YouTube. Results showed that participants' agreement with the satirical UGC was predicted by their political cynicism and political information efficacy, but not by candidate favorability. Watching the UGC satirizing the presidential candidates effected the favorability toward the male candidates but not the female candidate. In addition, the evidence suggested that the frequency of exposure to satirical UGC is related to political information efficacy, but not with political cynicism or candidate favorability.

An Analysis Method of User Preference by using Web Usage Data in User Device (사용자 기기에서 이용한 웹 데이터 분석을 통한 사용자 취향 분석 방법)

  • Lee, Seung-Hwa;Choi, Hyoung-Kee;Lee, Eun-Seok
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.3
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    • pp.189-199
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    • 2009
  • The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

Recognition of Human Typing Pattern Using Neural Network (신경망을 이용한 휴먼 타이핑 패턴 인식)

  • Bae, Jung-Gi;Kim, Byung-Whan;Lee, Sang-Kyu
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.449-451
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    • 2006
  • With the increasing danger of personal information being exposed, a technique to protect personal information by identifying a non-user in case it is exposed. A study to construct a neural network recognizer for developing a economical and effective user protecting system. For this, time variables regarding user typing patterns from a pattern extraction device. With the variations in the standard deviation for the collected time variables, non-user patterns were generated. The recognition performance increased with the increase in the standard deviation and a higher recognition was achieved at 2.5. Also, five types of training data were generated and the recognition performance was examined as a function of the number of non-user patterns. With the increase in non-suer patterns, the recognition error quantified in the root mean square error (RMSE) was reduced. The smallest RMSE was obtained at the type 5 and 90 non-user patterns. In overall, the type 3 model yielded the highest recognition accuracy Particularly, a perfect recognition of 100% was achieved at 45 non-user patterns.

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Path Generation Method of UAV Autopilots Using Max-Min Algorithm

  • Kwak, Jeonghoon;Sung, Yunsick
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1457-1463
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    • 2018
  • In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has found widespread application across a diverse range of fields and is also utilized for controlling unmanned aerial vehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult for the user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs a flight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally fly straight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVs may collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust the generated path taking the locations of the obstacles into consideration. This paper proposes a natural path generation method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, the proposed method generates paths that allow UAVs to avoid obstacles.

What Drives Consumers' Purchase Decisions? : User- and Marketer-generated Content

  • Kim, Yu-Jin
    • Science of Emotion and Sensibility
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    • v.24 no.4
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    • pp.79-90
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    • 2021
  • Consumers have an increasingly active role in the marketing cycle, using social media channels to create, distribute, and consume digital content. In this context, this paper investigates the impact of user- and marketer-generated content on consumer purchase intentions and the approach to designing an effective social media marketing platform. Referencing a literature review of social media marketing and consumer purchase intentions, a case study of the social media-marketing platform, 0.8L, was undertaken using both qualitative and quantitative results through content analysis and a participatory survey. First, about 450 consumer reviews for ten sunscreen products posted on the 0.8L platform were compared with products' marketer-generated content. Next, 55 subjects participated in a survey regarding purchase intentions toward moisturizing creams on the 0.8L platform. The results indicated that user-generated content (i.e., texts and photos) provided more personal experiences of the product usage process, whereas marketers focused on distinctive product photos and features. Moreover, customer reviews (particularly high volume and narrative format) had more impact on purchase decisions than marketer information in the online cosmetics market. Real users' honest reviews (both positive and negative) were found to aid companies' prompt and straightforward assessment of newly released products. In addition to the importance of customer-driven marketing practices, distinctive user experience design features of a competitive social media-marketing platform are identified to facilitate the creation and sharing of sincere customer reviews that resonate with potential buyers.

Credibility Assessment of Online Information in Context

  • Rieh, Soo Young
    • Journal of Information Science Theory and Practice
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    • v.2 no.3
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    • pp.6-17
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    • 2014
  • The purpose of this study is to examine to what extent the context in which people interact with online information affects people's credibility perceptions. In this study, credibility assessment is defined as perceptions of credibility relying on individuals' expertise and knowledge. Context has been characterized with respect to three aspects: Context as user goals and intentions, context as topicality of information, and context as information activities. The data were collected from two empirical studies. Study 1 was a diary study in which 333 residents in Michigan, U.S.A. submitted 2,471 diary entries to report their trust perceptions associated with ten different user goals and nine different intentions. Study 2 was a lab-based study in which 64 subjects participated in performing four search tasks in two different information activity conditions - information search or content creation. There are three major findings of this study: (1) Score-based trust perceptions provided limited views of people's credibility perceptions because respondents tended to score trust ratings consistently high across various user goals and intentions; (2) The topicality of information mattered more when study subjects assessed the credibility of user generated content (UGC) than with traditional media content (TMC); (3) Subjects of this study exerted more effort into making credibility judgments when they engaged in searching activities than in content creation. These findings indicate that credibility assessment can or should be seen as a process-oriented notion incorporating various information use contexts beyond simple rating-based evaluation. The theoretical contributions for information scientists and practical implications for web designers are also discussed.

User Query Processing Model in the Item Recommendation Agent for E-commerce (전자상거래를 위한 상품 추천 에이전트에서의 사용자 질의 처리 모델)

  • 이승수;이광형
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.244-246
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    • 2002
  • The rapid increase of E-commerce market requires a solution to assist the buyer to find his or her interested items. The intelligent agent model is one of the approaches to help the buyers in purchasing items in outline market. In this paper, the user query processing model in the item recommendation agent is proposed. In the proposed model, the retrieval result is affected by the automatically generated queries from user preference information as well as the queries explicitly given by user. Therefore, the proposed model can provide the customized search results to each user.

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