eWOM & Referrals in Social Network Services

If a few decades ago the development of the Internet was instrumental in the interconnection between markets, nowadays the services provided by Web 2.0, such as social network sites (SNS) are the cutting edge. A proof of this trend is the exponential growth of social network users. The main objective of this work is to explore the mechanisms that promote the transmission and reception (WOM and referrals) of online opinions, in the context of the SNS, by buyers of travel services. The research includes some research lines: technology acceptance model (TAM), Social Identification Theory and Word-of-Mouth communication in virtual environment (eWOM). Based on these theories an explicative model has been proposed applying SEM analysis to a sample of SNS users’ of tourist service buyers. The results support the majority of the hypotheses and some relevant practical and theoretical implications have been pointed out for tourist managers

Estimating the Monetary Value of Information Privacy in the Context of SNS

The dramatic growth of SNS has created a myriad of information privacy. To achieve our objective, first, this study estimates the monetary value of information privacy by using the CVM. Second, it is estimated how the monetary value of information privacy would change according to demographic information, SNS usage cycle information, the Characteristics of SNS users, and the SNS features. As a result, sensitive SNS users for information privacy have following characteristics: 30s, higher education, less Monthly Expenditure or far more monthly expenditure, lower SNS use ability, more number of followers, little event experiences, shorter SNS experience, higher account open limit level and privacy invasion experiences. Also, the total WTA mean is $28/number. The monetary value of information privacy according to SNS features have the following characteristics. Those who use private SNS, the value of Profile, Location information, and the purpose of Sharing and Friendship are more important

Nature or Nurture? An Analysis of Rational Addiction to Mobile Social Applications

Through the lens of rational addiction theory (Becker and Murphy, 1988), this study investigates whether addiction to mobile social apps should be viewed as a rational behavior rather than an uncontrollable, irrational disorder. To derive the analytical model, this study extends the rational addiction framework to include a utility-level network effect as the key factor that regulates the inter-temporal consumption of mobile social apps. Further, to validate empirically the rational addiction model in this context, we gathered and analyzed longitudinal panel data on the weekly app usage of thousands of smartphone users. The findings suggest that consistent with the rational addiction theory, users of mobile social apps are rational and forward-looking. They determine their current consumption based on both past and future consumption and the utility derived from network effects. However, the extent of rational addiction to mobile social apps varies considerably across diverse demographic groups and app categories

Impression management and formation on Facebook: A lens model approach

To extend research on online impression formation and warranting theory, the present investigation reports a Brunswick lens model analysis of Facebook profiles. Facebook users’ (N = 100) personality (i.e., extraversion, agreeableness, conscientiousness, neuroticism, openness) was self-reported. Facebook users’ profiles were then content analyzed for the presence and rate of 53 cues. Observers (N = 35), who were strangers to profile owners, estimated profile owner personality. Results indicate that observers could accurately estimate profile owners’ extraversion, agreeableness, and conscientiousness. For all personality traits except neuroticism, unique profile cues were diagnostic warrants of personality (i.e., indicative of profile owner personality and used to estimate personality by strangers). The results are discussed in relation to warranting theory, impression formation, and lens model research

잠재 심리학 변수 및 사회적 상호작용을 고려한 새로운 일반화된 이질적 데이터 모형

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2020. 8. 이종수.사회적 상호작용은 개인의 태도 및 의견, 개인의 선호, 그리고 개인의 행동에 중요한 영향을 미친다. 따라서 사회적 상호작용은 사회과학 분야에 매우 중요한 연구 대상이다. 사회적 상호작용은 크게 구전 효과와 관찰된 학습 두가지로 나눌 수 있다. 기존 경제학 분야의 선택 모형에서는 주로 관찰된 학습을 사회적 상호작용으로 간주하였다. 구전 효과는 태도나 행위의 경향성 분석에 많이 연구되어 왔지만 선택 모형에 고려하는 것은 어려움이 많았다. 그리고, 많은 선택모형에서 개인의 의사결정 과정을 더 잘 이해하고 모형의 예측력을 향상시키기 위해 개인의 잠재적 심리학 변수를 추가하고자 하였다. 사회적 상호작용이 개인의 심리학적 특성에 많은 영향을 미친다는 것은 이미 많은 연구를 통해서 입증되어 왔다. 하지만 사회적 상호작용이 개인의 잠재적 심리학 변수에 미치는 영향을 다룬 연구는 매우 드물었다. 또한, 개인의 행동 사이에 존재한 상관관계를 선택모형에 동시에 다루지 못하면 편향된 추정결과를 얻을 수 있다. 혼합형 종속변수를 동시에 추정하는 모형은 꾸준히 개발되어 왔지만 여기에 사회적 상호작용을 고려한 연구는 찾아보기 힘들다. 본 연구에서는 두가지 사회적 상호작용을 모두고려하는 다중 선택 모형을 제안하였다. 제안한 선택 모형은 사회적 상호작용을 고려할 수 있을 뿐만 아니라 내생적 다중 선택을 다룰 수 있으며 혼합적 종속변수까지 포함할 수 있다. 본 연구에서 먼저 시뮬레이션 분석을 통해서 모델의 유용성을 입증한 다음에 실증분석으로 기존 모델에서 확인할 수 없었던 사회적 상호작용이 개인의 행위에 미치는 영향을 분석하였다. 사회적 상호작용을 고려하지 않으면 추정된 결과가 편향될 수 있으며 변수의 계수를 과대 추정할 가능성이 있다는 것을 실증연구를 통해서 증명했다.Social interaction has enormous effect on individuals attitude and opinion, preferences, and behaviors. Social interaction is one of the most important study regions within social sciences. There are generally two types of social interaction: word-of-mouth and observed learning. Observed learning is considered as social interaction is majority of choice models in economic studies. However, word-of-mouth is largely studied in attitude and behavior propensity related studies and hardly ever been incorporated in choice models due to the characteristics of the word-of-mouth. On the other hand, choice models have tried to incorporate individuals psychological variables in order to get better understanding of individual decision process and to improve the forecasting ability of the models. However, there are limited studies have considered the effect of social interaction on the individuals psychological variables which is one of the major mechanisms of social interaction. Moreover, since individuals behaviors endogenously correlated themselves, consideration of endogenously correlated outcomes simultaneously is necessary for many choice situations. Though there are some studies derived handful model for multiple choices, only a few models have incorporated the social interaction into the model. This study proposes a new multiple endogenous choice model incorporating both types of social interaction. Furthermore, the proposed model is capable of dealing with multiple endogenous heterogenous dependent variables. The dissertation conducts a simulation study to confirm the performance of proposed model and an empirical study to provide evidence of how social interaction effect on individuals choice and proof that ignoring the effect of social interactions may leads to inconsistent estimation and may over-estimated the variable effects.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Object 4 1.3 Research Outline 8 Chapter 2. Literature Review 10 2.1 Theoretical Insights 10 2.1.1 Studies on Human Behavior 11 2.1.2 Studies on Word-of-Mouth 14 2.2 Choice Models 20 2.2.1 Choice Models with Psychological Factors 20 2.2.2 Choice Models with Spatial/Social Dependence 32 2.2.3 Models of Mixed Data 41 2.3 Limitations of Previous Research and Research Motivation 46 Chapter 3. Model Specification 48 3.1 Latent Psychological Variable Structural Equation Model 49 3.2 Latent Variable Measurement Equation Model 50 3.2.1 Single Dependent Variable 50 3.2.2 Multiple Dependent Variables 52 3.3 Estimation Methodology 60 3.4 Simulation Study 62 3.4.1 Simulation Design 62 3.4.2 Simulation Results 65 Chapter 4. Empirical Study 73 4.1 Empirical Study Background and Specification 73 4.1.1 Latent Psychological Variables 75 4.1.2 Endogenous Outcomes 78 4.2 Data Description 80 4.3 Estimation Results 87 4.3.1 Structural Equation Model for Latent Psychological Variables 87 4.3.2 Effect of Latent Psychological Variables on Endogenous Outcomes 90 4.3.3 Comparison of the GHDM models 96 Chapter 5. Conclusion 100 5.1 Concluding Remarks and Contribution 100 5.2 Limitations and Future Studies 103Docto

Diff-Privacy: Diffusion-based Face Privacy Protection

Privacy protection has become a top priority as the proliferation of AI techniques has led to widespread collection and misuse of personal data. Anonymization and visual identity information hiding are two important facial privacy protection tasks that aim to remove identification characteristics from facial images at the human perception level. However, they have a significant difference in that the former aims to prevent the machine from recognizing correctly, while the latter needs to ensure the accuracy of machine recognition. Therefore, it is difficult to train a model to complete these two tasks simultaneously. In this paper, we unify the task of anonymization and visual identity information hiding and propose a novel face privacy protection method based on diffusion models, dubbed Diff-Privacy. Specifically, we train our proposed multi-scale image inversion module (MSI) to obtain a set of SDM format conditional embeddings of the original image. Based on the conditional embeddings, we design corresponding embedding scheduling strategies and construct different energy functions during the denoising process to achieve anonymization and visual identity information hiding. Extensive experiments have been conducted to validate the effectiveness of our proposed framework in protecting facial privacy.Comment: 17page

Communicating Validity Information to Differentially Experienced Audiences: The Effects of Numeracy and Nontraditional Metrics

One of the biggest challenges facing organizational researchers is convincing practitioners to adopt evidence-based personnel selection practices such as the structured interview. In this study, we examined the effects of nontraditional validity metrics and numeracy by presenting validity information about the structured interview to audiences with differing amounts of interview experience (students, working adults, and hiring managers). The results indicated that nontraditional metrics were associated with higher understanding, more positive attitudes, and greater perceptions of the usefulness of the structured interview. These effects were constant across differing levels of numeracy. Additionally, the results revealed that nontraditional metrics result in more positive perceptions because they facilitate greater understanding. Nontraditional metrics were, however, less effective when audiences had interview experience. These results can be leveraged by practitioners and researchers who are interested in more effectively communicating validity information about the structured interview

Adaptive Probability Theory: Human Biases as an Adaptation

Humans make mistakes in our decision-making and probability judgments. While the heuristics used for decision-making have been explained as adaptations that are both efficient and fast, the reasons why people deal with probabilities using the reported biases have not been clear. We will see that some of these biases can be understood as heuristics developed to explain a complex world when little information is available. That is, they approximate Bayesian inferences for situations more complex than the ones in laboratory experiments and in this sense might have appeared as an adaptation to those situations. When ideas as uncertainty and limited sample sizes are included in the problem, the correct probabilities are changed to values close to the observed behavior. These ideas will be used to explain the observed weight functions, the violations of coalescing and stochastic dominance reported in the literature