• Title/Summary/Keyword: Social Web

Search Result 1,076, Processing Time 0.031 seconds

Prediction Method for the Implicit Interpersonal Trust Between Facebook Users (페이스북 사용자간 내재된 신뢰수준 예측 방법)

  • Song, Hee Seok
    • Journal of Information Technology Applications and Management
    • /
    • v.20 no.2
    • /
    • pp.177-191
    • /
    • 2013
  • Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore. it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method. we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

Social Media Advertising Effectiveness: A Conceptual Framework and Empirical Validation

  • Liguo Lou;Joon Koh
    • Asia pacific journal of information systems
    • /
    • v.28 no.3
    • /
    • pp.183-203
    • /
    • 2018
  • In the era of Web 2.0, social media advertising can simultaneously stimulate consumers' brand purchase intention and brand information sharing intention. Product sales and brand information diffusion are equally important for a company that conducts advertising. This study investigates how features of brand content influence social media advertising effectiveness by integrating the stimulus-organism-response model and classic advertising effectiveness models. An analysis of 267 survey questionnaires shows that brand content-related cues, including perceived uniqueness, perceived vividness, and perceived interactivity have significant effects on consumers' affective and cognitive involvement, which then affect their attitude toward brand content. As a result, the consumers' attitude toward the brand and their brand purchase intention, as well as their brand content sharing intention, are positively affected by attitude toward brand content. This study contributes to a better understanding of how social advertising works, which suggests that managers should effectively use social media to conduct advertising.

An Analysis of Factors Influencing the Intention to Use Social Network Services (소셜 네트워크 서비스의 사용의도에 영향을 미치는 요인)

  • Kim, Jongki;Kim, Jinsung
    • Informatization Policy
    • /
    • v.18 no.3
    • /
    • pp.25-49
    • /
    • 2011
  • As a way to gather diverse information required for everyday living, the importance of social networks has been growing. Social network services have been spreading rapidly because of diffusion of the Internet, evolution of social network sites, and recognition of the importance of social networks. Recently, the social network service has been evolved based on a new paradigm, Web 2.0, pursuing participation and openness. Following the adoption of Web 2.0 technologies, the social network service allows users to make and maintain new relationships in a more convenient way. Users of the social network service tend to reveal their personal information, and share their ideas and content with other people; in the process they become aware of their existence, feel satisfaction with life and exert influence to others as a member of the society. This study uses higher order factor analysis to analyze factors that affect the intention of using the social network service. A research model was developed with second-order factors including perceived social presence, perceived gratification and perceived social influence. First-order factors are grouped by technical, individual and social factors. Smart PLS 2.0 was used to conduct empirical analysis. The analysis results supported the validity of the research model.

  • PDF

The Role of Subjective Well Bing in Internet Continuance (인터넷의 지속적 이용에 있어서 주관적안녕감의 역할)

  • Kwon, Soon-Jae
    • 한국IT서비스학회:학술대회논문집
    • /
    • 2009.11a
    • /
    • pp.73-82
    • /
    • 2009
  • Although the Internet has been a important communication tool in modern societies, researchers did not pay attention to its' positive impacts on individual's psychological process. The Internet provides users with a unique environment such as visual isolation, non face-to-face communication, and easiness to escape from social influences. This environment enables people to take free action according to their personality and disclose themselves. From the uses and gratification perspective, the current research reveals that individuals with high extraversion are inclined to maintain social networking sites and those with high openness participate in web communities. The findings indicate that individuals' social use of the Internet may reflect their personality. To fill the research void like this, this study proposes a new research model in which well bing as well as perceived value are positively linked to satisfaction and continuance to use. The statistical results obtained by applying PLS to the valid 150 questionnaires showed that the well bing has stronger positive influence on satisfaction and continuance to use than the perceived value. Therefore, a practical implication is suggested that the web site need to be designed in a way of arousing users' well bing more strongly.

  • PDF

Evaluating Conversion Rate from Advertising in Social Media using Big Data Clustering

  • Alyoubi, Khaled H.;Alotaibi, Fahd S.
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.7
    • /
    • pp.305-316
    • /
    • 2021
  • The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

An Empirical Study on Individual and Social Commerce Factors Impacting Shopping Value and Intention to Repurchase in Social Commerce and Moderating Effects of Perceived Security (소셜커머스의 쇼핑 가치와 재구매의도에 영향을 미치는 개인 및 소셜커머스 특성과 지각된 보안의 조절효과에 대한 연구)

  • Kim, Sanghyun;Park, HyunSun
    • Journal of Information Technology Services
    • /
    • v.12 no.2
    • /
    • pp.31-53
    • /
    • 2013
  • Web 2.0 has affected existing e-commerce and created a new business model of e-commerce, known as social commerce. Social commerce is a subset of e-commerce using social network services and is emerging as an important platform due to increased popularity of social networking services. This study focuses on analyzing the factors that influence the shopping value and intention to repurchase of social commerce users. Based on prior researches, we develop a research model, including individual characteristics of social commerce users (Collectivism, Price Sensitivity, Impulse Buying) and social commerce characteristics (Cost saving, Product Variety, Shopping Convenience). Furthermore, this study proposed the moderating effect of Perceived Security and the relationship between shopping value and intention to repurchase. To empirically validate, the data were collected from 220 social commerce users. The results indicated that individual characteristics (collectivism, price sensitivity, impulse buying) were positively related to hedonic shopping value. In addition, social commerce characteristics (cost saving, shopping convenience) were positively related to utilitarian value. The shopping value(hedonic and utilitarian) had a significant influence on intention to repurchase. The moderating effects of perceived security also was significant. Lastly, the implications for theory and practice are discussed.

SAD : Web Session Anomaly Detection based on Bayesian Estimation (베이지언 추정을 이용한 웹 서비스 공격 탐지)

  • 조상현;김한성;이병희;차성덕
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.13 no.2
    • /
    • pp.115-125
    • /
    • 2003
  • As Web services are generally open for external uses and not filtered by Firewall, these result in attacker's target. Web attacks which exploit vulnerable web-applications and malicious users' requests cause economical and social problems. In this paper, we are modelling general web service usages based on user-web-session and detect anomal usages with Bayesian estimation method. Finally we propose SAD(Session Anomaly Detection) for detection unknown web attacks. To evaluate SAD, we made an experiment on attack simulation with web vulnerability scanner, whisker. The results show that the detection rate of SAD is over 90%, which is influenced by several features such as size of window or training set, detection filter method and web topology.

Targeting Data Service for Web-Based Media Contents (웹 기반 미디어 콘텐츠를 위한 맞춤형 데이터 서비스)

  • Park, Sung-Joo;Chung, Kwang-Sue
    • Journal of KIISE:Computing Practices and Letters
    • /
    • v.16 no.12
    • /
    • pp.1154-1164
    • /
    • 2010
  • As an useful application in broadcasting services, the targeting service has been mainly studied to improve the service satisfaction and user usage in various media service environments based on user profile, preferences, and usage history. Targeting service is expanding its domain from broadcasting contents to interstitial contents and from fixed TV devices to mobile devices. Service data also include advertisement data, coupon, and information about media contents as well as simple broadcasting data. In this paper, the targeting data service is designed and implemented on articles, advertisement and broadcasting information on the basis of the user information. To adapt this to web-based media contents, information on user profile, preferences, and usage history is newly defined on the basis of the user metadata developed in TV-Anytime Forum and the user information defined in OpenSocial. The targeting data service is implemented to generate user preferences information and usage history pattern based on the similarity among user preference, contents information, and usage history. Based on performance evaluation, we prove that the proposed targeting data service is effectively applicable to web-based media contents as well as broadcasting service.

Contents Recommendation Method Based on Social Network (소셜네트워크 기반의 콘텐츠 추천 방법)

  • Pei, Yun-Feng;Sohn, Jong-Soo;Chung, In-Jeong
    • The KIPS Transactions:PartB
    • /
    • v.18B no.5
    • /
    • pp.279-290
    • /
    • 2011
  • As the volume of internet and web contents have shown an explosive growth in recent years, lately contents recommendation system (CRS) has emerged as an important issue. Consequently, researches on contents recommendation method (CRM) for CRS have been conducted consistently. However, traditional CRMs have the limitations in that they are incapable of utilizing in web 2.0 environments where positions of content creators are important. In this paper, we suggest a novel way to recommend web contents of high quality using both degree of centrality and TF-IDF. For this purpose, we analyze TF-IDF and degree of centrality after collecting RSS and FOAF. Then we recommend contents using these two analyzed values. For the verification of the suggested method, we have developed the CRS and showed the results of contents recommendation. With the suggested idea we can analyze relations between users and contents on the entered query, and can consequently provide the appropriate contents to the user. Moreover, the implemented system we suggested in this paper can provide more reliable contents than traditional CRS because the importance of the role of content creators is reflected in the new system.