When Love Becomes Hate(?): The Interplay Between Consumer-Brand Relationships and Crisis Situations

This study had three purposes. First, it aimed to re-conceptualize organization-public relationships (OPRs) in public relations and crisis communication. This OPR re-conceptualization helps find out when the OPR buffering effect or the OPR love-becomes-hate effect happens. Second, it aimed to examine how consumer emotions are influenced by OPRs and influence consumer behavioral intentions. Third, it aimed to address the current problematic operationalization of the concept of consumer. Three pilot studies and one main study were conducted. Apple and Whole Foods were the two brands examined. One crisis that undermined the self-defining attributes shared between the brand and its consumers and another crisis that did not were examined for each brand. Almost 500 Apple consumers and 400 Whole Foods consumers provided usable questionnaires. This study had several major findings. First, non-identifying relationship and identifying relationship were different constructs. Moreover, trust, satisfaction, and commitment were not conceptually separate dimensions of OPRs. Second, the non-identifying relationships offered buffering effects by increasing positive attitudes and tempering anger and disappointment. The identifying relationships primarily offered the love-becomes-hate effects by increasing anger and disappointment. Third, if the crisis was relevant to consumers’ daily lives, brand response strategies were less effective at mitigating consumer negative reactions. Moreover, apology-compensation-reminder strategy was more effective compared to no-comment strategy. However, the apology-compensation-reminder strategy was no more effective than other strategies as long as brands compensate to the victims. Identifying relationships increased the effectiveness of response strategies. If the crisis did not undermine the self-defining attributes shared between consumers and brands, the response strategies worked even better. This study contributes to crisis communication research in multiple ways. First, it advances the OPR conceptualization by demonstrating that non-identifying relationship and identifying relationship are different concepts. More importantly, it advances the theory building of OPRs’ influences on crises by finding out when the buffering effect and the love-becomes-hate effect happen. Second, it adds to emotion research by demonstrating that strong OPRs can lead to negative emotions and positive emotions can have negative behavioral consequences on organizations. Third, the precise operationalization of the concept of consumer gives more insights about consumer reactions to crises.

Childhood Attention Problems and the Development of Comorbid Symptoms at the Transition to High School: The Mediating Role of Parent and Peer Relationships

Children with Attention-Deficit/Hyperactivity Disorder (ADHD) are at increased risk for the development of depression and delinquent behavior. Children and adolescents with ADHD also experience difficulty creating/maintaining high quality friendships and parent-child relationships, and these difficulties may contribute to the development of co-morbid internalizing and externalizing symptoms in adolescence. However, there is limited research examining whether high quality friendships and parent-child relationships mediate the relation between ADHD and the emergence of these co-morbid symptoms at the transition to high school. This study examines the mediating role of relationship quality in the association between ADHD and depressive symptoms/delinquent behaviors at this developmentally significant transition point. Results revealed significant indirect effects of grade 6 attention problems on grade 9 depressive symptoms through friendship quality and quality of the mother-child relationship in grade 8. Interventions targeting parent and peer relationships may be valuable for youth with ADHD to promote successful transitions to high school.

ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS

Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.

The role of new information and communication technologies (ICTs) in information and communication in science. A conceptual framework and empirical study

Problem This dissertation presents a literature-based framework for communication in science (with the elements partners, purposes, message, and channel), which it then applies in and amends through an empirical study of how geoscientists use two social computing technologies (SCTs), blogging and Twitter (both general use and tweeting from conferences). How are these technologies used and what value do scientists derive from them? Method The empirical part used a two-pronged qualitative study, using (1) purposive samples of ~400 blog posts and ~1000 tweets and (2) a purposive sample of 8 geoscientist interviews. Blog posts, tweets, and interviews were coded using the framework, adding new codes as needed. The results were aggregated into 8 geoscientist case studies, and general patterns were derived through cross-case analysis. Results A detailed picture of how geoscientists use blogs and twitter emerged, including a number of new functions not served by traditional channels. Some highlights: Geoscientists use SCTs for communication among themselves as well as with the public. Blogs serve persuasion and personal knowledge management; Twitter often amplifies the signal of traditional communications such as journal articles. Blogs include tutorials for peers, reviews of basic science concepts, and book reviews. Twitter includes links to readings, requests for assistance, and discussions of politics and religion. Twitter at conferences provides live coverage of sessions. Conclusions Both blogs and Twitter are routine parts of scientists' communication toolbox, blogs for in-depth, well-prepared essays, Twitter for faster and broader interactions. Both have important roles in supporting community building, mentoring, and learning and teaching. The Framework of Communication in Science was a useful tool in studying these two SCTs in this domain. The results should encourage science administrators to facilitate SCT use of scientists in their organization and information providers to search SCT documents as an important source of information.

Structured Approaches for Exploring Interpersonal Relationships in Natural Language Text

Human relationships have long been studied by scientists from domains like sociology, psychology, literature, etc. for understanding people's desires, goals, actions and expected behaviors. In this dissertation we study inter-personal relationships as expressed in natural language text. Modeling inter-personal relationships from text finds application in general natural language understanding, as well as real-world domains such as social networks, discussion forums, intelligent virtual agents, etc. We propose that the study of relationships should incorporate not only linguistic cues in text, but also the contexts in which these cues appear. Our investigations, backed by empirical evaluation, support this thesis, and demonstrate that the task benefits from using structured models that incorporate both types of information. We present such structured models to address the task of modeling the nature of relationships between any two given characters from a narrative. To begin with, we assume that relationships are of two types: cooperative and non-cooperative. We first describe an approach to jointly infer relationships between all characters in the narrative, and demonstrate how the task of characterizing the relationship between two characters can benefit from including information about their relationships with other characters in the narrative. We next formulate the relationship-modeling problem as a sequence prediction task to acknowledge the evolving nature of human relationships, and demonstrate the need to model the history of a relationship in predicting its evolution. Thereafter, we present a data-driven method to automatically discover various types of relationships such as familial, romantic, hostile, etc. Like before, we address the task of modeling evolving relationships but don't restrict ourselves to two types of relationships. We also demonstrate the need to incorporate not only local historical but also global context while solving this problem. Lastly, we demonstrate a practical application of modeling inter-personal relationships in the domain of online educational discussion forums. Such forums offer opportunities for its users to interact and form deeper relationships. With this view, we address the task of identifying initiation of such deeper relationships between a student and the instructor. Specifically, we analyze contents of the forums to automatically suggest threads to the instructors that require their intervention. By highlighting scenarios that need direct instructor-student interactions, we alleviate the need for the instructor to manually peruse all threads of the forum and also assist students who have limited avenues for communicating with instructors. We do this by incorporating the discourse structure of the thread through latent variables that abstractly represent contents of individual posts and model the flow of information in the thread. Such latent structured models that incorporate the linguistic cues without losing their context can be helpful in other related natural language understanding tasks as well. We demonstrate this by using the model for a very different task: identifying if a stated desire has been fulfilled by the end of a story.

Happy and Other Stories

The characters in “Happy,” “The Price of Independence,” “Itch,” and “Guillotine” all struggle with their loss of power and ability to successfully navigate their own lives. Though different genders, ages, and worlds are rendered each character must choose to either face their conflict head on or submit to the external pressure present. “The Price of Independence” and “Itch” highlight the precariousness of relationships and how one relationship, whether it be romantic or platonic, can change everything. “Happy” and “Guillotine” feature characters struggling from within, they are separated from the world around them and their failures force a spotlight on the misconceptions of mental health care.