Matching Items (23)
Filtering by
- Creators: Arizona State University
Description
The current study is the first qualitative investigation aimed solely at understanding what it means to communicate conditional forgiveness in serious romantic relationships. Conditional forgiveness is forgiveness that has been offered with the stipulation that the errant behavior cease. It is a provocative topic because some argue genuine forgiveness is not conditional, but recent discoveries that have associated its use with severe transgressions and relational deterioration suggest it is a critical site for investigation. This inductive analysis of open-ended data from 201 anonymous surveys identified both distinctions between and intersections of conditional forgiveness, forgiveness, and reconciliation. A relational dialectics analysis also revealed that reconcilable-irreconcilable was the overarching tension for conditional forgivers and six additional tensions also were also discovered: individual identity-couple identity, safety-risk, certainty-uncertainty, mercy-justice, heart-mind, and expression-suppression. Of particular intrigue, the current analysis supports the previous discovery of implicit conditional forgiveness--suppressing conditions, sometimes in response to physical and substance abuse. Ultimately, the current analysis contributes to the enduring conversation aimed at understanding the communication and pursuit of forgiveness and reconciliation. It addresses one of the basic instincts and paradoxes of existing with others--the balance between vulnerability and protection.
ContributorsKloeber, Dayna Noel (Author) / Waldron, Vincent R. (Thesis advisor) / Kelley, Douglas L. (Committee member) / Kassing, Jeffrey W. (Committee member) / Fisher, Carla L. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The division of domestic labor has far-reaching implications for "private" life (e.g. relational satisfaction and conflict) and for "public" paid labor (e.g. time and dedication in the workplace and career advancement). Although several theories have been developed and tested, they do not sufficiently explain the consistent findings that women in mixed sex households perform a majority of the domestic labor. Without understanding the causes for differences in task performance, past research encouraging communicative solutions to ameliorate conflict was ineffective in changing task allocation and performance. Therefore, it is necessary to understand theoretical explanations that drive domestic labor behavior to develop effective solutions. The recent integrative theory of the division of domestic labor attempts to explain how individuals interact with household partners to allocate domestic tasks. Recognizing the complexity of the division of domestic labor, the integrative theory considers individual, dyadic, and societal factors that influence task allocation. Because clear differences in task performance have been found in mixed sex households, this study separates sex and gender as distinct variables by considering same-sex roommate relationships, essentially removing sex differences from the living arrangement. Furthermore, this study considers individual threshold levels as described by the integrative theory in order to test the theoretical underpinnings. Specifically, this study is designed to investigate the relationships between individual cleanliness threshold levels and gender, sex, perceptions of satisfaction, equity, and frequency of conflict in same-sex roommate relationships. Results indicate support of the integrative theory of the division of domestic labor. Regarding gender differences, partial support for the theory appeared in that feminine individuals have lower threshold levels than masculine individuals. Regarding sex differences, women possess lower individual threshold levels (i.e. more bothered when a task is undone) compared to men, which likely accounts for why existing research indicates that women spend more time performing domestic tasks. What is more, individuals with higher threshold levels report greater relational satisfaction. Further, individuals whose threshold levels differ from their living partner report lower relational satisfaction and greater conflict frequency. Finally, in terms of equity, both overbenefited and underbenefited individuals experience more conflict than those who feel their relationship is equitable. These results provide theoretical support for the integrative theory of the division of labor. Furthermore, the development and testing of a threshold measure scale can be used practically for future research and for better roommate pairings by universities. In addition, communication scholars, family practitioners and counselors, and universities can apply these theoretically grounded research findings to develop and test strategies to reduce conflict and increase relational satisfaction among roommates and couples.
ContributorsRiforgiate, Sarah (Author) / Alberts, Jess K. (Thesis advisor) / Mongeau, Paul (Thesis advisor) / Roberto, Anthony (Committee member) / Romero, Mary (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis deals with the analysis of interpersonal communication dynamics in online social networks and social media. Our central hypothesis is that communication dynamics between individuals manifest themselves via three key aspects: the information that is the content of communication, the social engagement i.e. the sociological framework emergent of the communication process, and the channel i.e. the media via which communication takes place. Communication dynamics have been of interest to researchers from multi-faceted domains over the past several decades. However, today we are faced with several modern capabilities encompassing a host of social media websites. These sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information, our modes of social engagement, and mechanisms of how the media characteristics impact our interactional behavior. The outcomes of this research are manifold. We present our contributions in three parts, corresponding to the three key organizing ideas. First, we have observed that user context is key to characterizing communication between a pair of individuals. However interestingly, the probability of future communication seems to be more sensitive to the context compared to the delay, which appears to be rather habitual. Further, we observe that diffusion of social actions in a network can be indicative of future information cascades; that might be attributed to social influence or homophily depending on the nature of the social action. Second, we have observed that different modes of social engagement lead to evolution of groups that have considerable predictive capability in characterizing external-world temporal occurrences, such as stock market dynamics as well as collective political sentiments. Finally, characterization of communication on rich media sites have shown that conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Based on all these outcomes, we believe that this research can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.
ContributorsDe Choudhury, Munmun (Author) / Sundaram, Hari (Thesis advisor) / Candan, K. Selcuk (Committee member) / Liu, Huan (Committee member) / Watts, Duncan J. (Committee member) / Seligmann, Doree D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Since the September 11, 2001 terrorist attacks and subsequent creation of the Transportation Security Administration (TSA), airport security has become an increasingly invasive, cumbersome, and expensive process. Fraught with tension and discomfort, "airport security" is a dirty phrase in the popular imagination, synonymous with long lines, unimpressive employees, and indignity. In fact, the TSA and its employees have featured as topic and punch line of news and popular culture stories. This image complicates the TSA's mission to ensure the nation's air travel safety and the ways that its officers interact with passengers. Every day, nearly two million people fly domestically in the United States. Each passenger must interact with many of the approximately 50,000 agents in airports. How employees and travelers make sense of interactions in airport security contexts can have significant implications for individual wellbeing, personal and professional relationships, and organizational policies and practices. Furthermore, the meaning making of travelers and employees is complexly connected to broad social discourses and issues of identity. In this study, I focus on the communication implications of identity and emotional performances in airport security in light of discourses at macro, meso, and micro levels. Using discourse tracing (LeGreco & Tracy, 2009), I construct the historical and discursive landscape of airport security, and via participant observation and various types of interviews, demonstrate how officers and passengers develop and perform identity, and the resulting interactional consequences. My analysis suggests that passengers and Transportation Security Officers (TSOs) perform three main types of identities in airport security contexts--what I call Stereotypical, Ideal, and Mindful--which reflect different types and levels of discourse. Identity performances are intricately related to emotional processes and occur dynamically, in relation to the identity and emotional performances of others. Theoretical implications direct attention to the ways that identity and emotional performances structure interactions, cause burdensome emotion management, and present organizational actors with tension, contradiction, and paradox to manage. Practical implications suggest consideration of passenger and TSO emotional wellbeing, policy framing, passenger agency, and preferred identities. Methodologically, this dissertation offers insight into discourse tracing and challenges of embodied "undercover" research in public spaces.
ContributorsRedden, Shawna Malvini (Author) / Tracy, Sarah J. (Thesis advisor) / Corley, Kevin (Committee member) / Alberts, Janet (Committee member) / Trethewey, Angela (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study described the multimodal communication patterns of college students and their parents, and examined how face-to-face and mediated communication frequencies relate to parental idealization and relational quality. Undergraduate students (N = 678) completed an online survey that assessed indicators of idealization (idealistic distortion and positive affect thinking), relational quality (relational/communication satisfaction, and relational closeness), and the frequency of face-to-face and mediated parental communication. Results indicated that average college students communicate with their primary parent 23 times per week, mostly via phone calls, text messaging, and face-to-face interaction. The frequency of mediated communication was positively related to both indicators of idealization and both indicators of relational quality. Moreover, idealization partially mediated the relationship between mediated communication frequency and relational quality. The frequency of face-to-face communication was inversely related to positive affect thinking. Indirect effects were also detected, such that face-to-face communication was negatively related to both indicators of relational quality as a function of positive affect thinking. Finally, this study examined whether students experience different levels of parental idealization and relational quality depending on whether their parent is geographically close or geographically distant, and whether they reside with their parent. Results indicated that students who live geographically distant from their parent experienced greater levels of idealization and relational quality than did student who live geographically close to yet separate from their parent, who reported greater levels of idealization and relational quality than students who live with their parent. These results were interpreted using concepts from interpersonal, family, and computer-mediated communication. Limitations and directions for future research were discussed.
ContributorsBryant, Erin M (Author) / Ramirez Jr., Artemio (Thesis advisor) / Floyd, Kory (Committee member) / Valiente, Carlos (Committee member) / Arizona State University (Publisher)
Created2012
Description
Social situational awareness, or the attentiveness to one's social surroundings, including the people, their interactions and their behaviors is a complex sensory-cognitive-motor task that requires one to be engaged thoroughly in understanding their social interactions. These interactions are formed out of the elements of human interpersonal communication including both verbal and non-verbal cues. While the verbal cues are instructive and delivered through speech, the non-verbal cues are mostly interpretive and requires the full attention of the participants to understand, comprehend and respond to them appropriately. Unfortunately certain situations are not conducive for a person to have complete access to their social surroundings, especially the non-verbal cues. For example, a person is who is blind or visually impaired may find that the non-verbal cues like smiling, head nod, eye contact, body gestures and facial expressions of their interaction partners are not accessible due to their sensory deprivation. The same could be said of people who are remotely engaged in a conversation and physically separated to have a visual access to one's body and facial mannerisms. This dissertation describes novel multimedia technologies to aid situations where it is necessary to mediate social situational information between interacting participants. As an example of the proposed system, an evidence-based model for understanding the accessibility problem faced by people who are blind or visually impaired is described in detail. From the derived model, a sleuth of sensing and delivery technologies that use state-of-the-art computer vision algorithms in combination with novel haptic interfaces are developed towards a) A Dyadic Interaction Assistant, capable of helping individuals who are blind to access important head and face based non-verbal communicative cues during one-on-one dyadic interactions, and b) A Group Interaction Assistant, capable of provide situational awareness about the interaction partners and their dynamics to a user who is blind, while also providing important social feedback about their own body mannerisms. The goal is to increase the effective social situational information that one has access to, with the conjuncture that a good awareness of one's social surroundings gives them the ability to understand and empathize with their interaction partners better. Extending the work from an important social interaction assistive technology, the need for enriched social situational awareness is everyday professional situations are also discussed, including, a) enriched remote interactions between physically separated interaction partners, and b) enriched communication between medical professionals during critical care procedures, towards enhanced patient safety. In the concluding remarks, this dissertation engages the readers into a science and technology policy discussion on the potential effect of a new technology like the social interaction assistant on the society. Discussing along the policy lines, social disability is highlighted as an important area that requires special attention from researchers and policy makers. Given that the proposed technology relies on wearable inconspicuous cameras, the discussion of privacy policies is extended to encompass newly evolving interpersonal interaction recorders, like the one presented in this dissertation.
ContributorsKrishna, Sreekar (Author) / Panchanathan, Sethuraman (Thesis advisor) / Black, John A. (Committee member) / Qian, Gang (Committee member) / Li, Baoxin (Committee member) / Shiota, Michelle (Committee member) / Arizona State University (Publisher)
Created2011
Description
In a mere thirty years, hospice has grown from a purely ideological philosophy of care for terminally ill individuals and their families, to a large and well organized healthcare entity. And government statistics project that healthcare will generate more new jobs than any other industry in America until at least 2018. While most of the extant literature that has been published on healthcare workers has focused on negative organizational processes, such as stress and burnout, there has been a recent shift in scholarly ideology in which researchers have been challenged to consider the positive aspects of organizational life as well. Compassion, theorized as a three-part interrelated process, is one area that is garnering interest within organizational studies. Utilizing grounded theory, this study engaged literature from organizational studies on emotional labor, stress, and burnout, as well as literature on positive organizational communication. What emerged from the data is a richly detailed picture of the emotional highs and lows that hospice workers experience in their jobs. Research was conducted at two large hospices in the desert southwest, utilized qualitative methods of participant observation (161 hours), and informal and semi-structured interviews (29 interviews) as a means to understand hospice workers--nurses (32), nursing assistants (23), social workers (14), and spiritual care providers (4)--experiences of emotion. Through data analysis, compassion emerged as a salient concept in worker's daily experiences. Yet, my data suggested a reconceptualization of the way in which compassion has been theorized in the past--as noticing, feeling, and responding. Based on my findings, I argue that the three subprocesses could more accurately be described recognizing, relating, and responding.
ContributorsWay, Deborah (Author) / Tracy, Sarah J. (Thesis advisor) / Carlson, Cheree (Committee member) / Kastenbaum, Robert (Committee member) / Arizona State University (Publisher)
Created2010
Description
The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to study the behavior of individuals online (content analysis) and 2) Synthesis: to build models that influence the behavior of individuals offline (incomplete action models for decision-making).
A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data.
The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners.
A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data.
The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners.
ContributorsManikonda, Lydia (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Li, Baoxin (Committee member) / De Choudhury, Munmun (Committee member) / Kamar, Ece (Committee member) / Arizona State University (Publisher)
Created2019
Description
In recent years, the rise in social media usage both vertically in terms of the number of users by platform and horizontally in terms of the number of platforms per user has led to data explosion.
User-generated social media content provides an excellent opportunity to mine data of interest and to build resourceful applications. The rise in the number of healthcare-related social media platforms and the volume of healthcare knowledge available online in the last decade has resulted in increased social media usage for personal healthcare. In the United States, nearly ninety percent of adults, in the age group 50-75, have used social media to seek and share health information. Motivated by the growth of social media usage, this thesis focuses on healthcare-related applications, study various challenges posed by social media data, and address them through novel and effective machine learning algorithms.
The major challenges for effectively and efficiently mining social media data to build functional applications include: (1) Data reliability and acceptance: most social media data (especially in the context of healthcare-related social media) is not regulated and little has been studied on the benefits of healthcare-specific social media; (2) Data heterogeneity: social media data is generated by users with both demographic and geographic diversity; (3) Model transparency and trustworthiness: most existing machine learning models for addressing heterogeneity are considered as black box models, not many providing explanations for why they do what they do to trust them.
In response to these challenges, three main research directions have been investigated in this thesis: (1) Analyzing social media influence on healthcare: to study the real world impact of social media as a source to offer or seek support for patients with chronic health conditions; (2) Learning from task heterogeneity: to propose various models and algorithms that are adaptable to new social media platforms and robust to dynamic social media data, specifically on modeling user behaviors, identifying similar actors across platforms, and adapting black box models to a specific learning scenario; (3) Explaining heterogeneous models: to interpret predictive models in the presence of task heterogeneity. In this thesis, novel algorithms with theoretical analysis from various aspects (e.g., time complexity, convergence properties) have been proposed. The effectiveness and efficiency of the proposed algorithms is demonstrated by comparison with state-of-the-art methods and relevant case studies.
User-generated social media content provides an excellent opportunity to mine data of interest and to build resourceful applications. The rise in the number of healthcare-related social media platforms and the volume of healthcare knowledge available online in the last decade has resulted in increased social media usage for personal healthcare. In the United States, nearly ninety percent of adults, in the age group 50-75, have used social media to seek and share health information. Motivated by the growth of social media usage, this thesis focuses on healthcare-related applications, study various challenges posed by social media data, and address them through novel and effective machine learning algorithms.
The major challenges for effectively and efficiently mining social media data to build functional applications include: (1) Data reliability and acceptance: most social media data (especially in the context of healthcare-related social media) is not regulated and little has been studied on the benefits of healthcare-specific social media; (2) Data heterogeneity: social media data is generated by users with both demographic and geographic diversity; (3) Model transparency and trustworthiness: most existing machine learning models for addressing heterogeneity are considered as black box models, not many providing explanations for why they do what they do to trust them.
In response to these challenges, three main research directions have been investigated in this thesis: (1) Analyzing social media influence on healthcare: to study the real world impact of social media as a source to offer or seek support for patients with chronic health conditions; (2) Learning from task heterogeneity: to propose various models and algorithms that are adaptable to new social media platforms and robust to dynamic social media data, specifically on modeling user behaviors, identifying similar actors across platforms, and adapting black box models to a specific learning scenario; (3) Explaining heterogeneous models: to interpret predictive models in the presence of task heterogeneity. In this thesis, novel algorithms with theoretical analysis from various aspects (e.g., time complexity, convergence properties) have been proposed. The effectiveness and efficiency of the proposed algorithms is demonstrated by comparison with state-of-the-art methods and relevant case studies.
ContributorsNelakurthi, Arun Reddy (Author) / He, Jingrui (Thesis advisor) / Cook, Curtiss B (Committee member) / Maciejewski, Ross (Committee member) / Tong, Hanghang (Committee member) / Arizona State University (Publisher)
Created2019
Description
College sports in America represent a multibillion dollar industry. Recruiting collegiate student-athletes not only is costly for university teams, but is integral for their long-term success. Universities spend substantial amounts of money to recruit student-athletes, yet relatively little academic work has focused on understanding the athletic recruiting process. While NCAA policy regulates when communication is allowed between coaches and student-athletes, there is a lack of literature investigating what the communicative aspects of athletic recruiting entail. Thus, the purpose of this dissertation is to unpack the student-athlete experience of collegiate athletic recruitment. It builds on theoretical work from organizational and interpersonal communication, as well as management and marketing, to extend existing knowledge of student-athletes’ college choice. Specifically, a conceptual model is presented that includes how student-athletes’ expectations and relationships during athletic recruitment contribute to an overall affinity for the university that, in turn, influences choice.
Thirty Division I student-athletes from six different sports participated in focus groups to discuss their recruitment experiences. Taking a grounded theory approach to the focus group transcripts, thematic analysis illuminated what was most memorable for student-athletes about their recruitment, what expectations they had for the process, and what relational benefits they sought when making their college choice decision. Findings reinforced the prominence of communication in the recruitment process, and indicated the importance of interpersonal relationships, authentic communication, and a customized recruiting experience. This work represents the start of a scholarly trajectory which will further conceptualize and test the relational elements of athletic recruiting. Future directions, as well as theoretical and practical implications, are discussed.
Thirty Division I student-athletes from six different sports participated in focus groups to discuss their recruitment experiences. Taking a grounded theory approach to the focus group transcripts, thematic analysis illuminated what was most memorable for student-athletes about their recruitment, what expectations they had for the process, and what relational benefits they sought when making their college choice decision. Findings reinforced the prominence of communication in the recruitment process, and indicated the importance of interpersonal relationships, authentic communication, and a customized recruiting experience. This work represents the start of a scholarly trajectory which will further conceptualize and test the relational elements of athletic recruiting. Future directions, as well as theoretical and practical implications, are discussed.
ContributorsPosteher, Karlee A (Author) / Kassing, Jeffrey W. (Thesis advisor) / Mongeau, Paul A. (Thesis advisor) / Mandel, Naomi (Committee member) / Arizona State University (Publisher)
Created2019