Matching Items (3)
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- All Subjects: Interpersonal communication
- Creators: Randall, Ashley K.
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
Individuals in a romantic relationship may avoid discussing certain topics with their partner, often to avoid relational and emotional risk. This strategy is known as topic avoidance and may be an important factor for individuals in turbulent romantic relationship to consider due to the importance of communicating with a partner. The associations between characteristics such as openness, relationship satisfaction, and perceived partner unresponsiveness, and topic avoidance have not been directly studied within dogmatism literature. However, dogmatism, defined as a person’s relative openness (or closedness) to new information, may be an important construct associated with topic avoidance that strengthens the associations between perceived partner unresponsiveness, and topic avoidance, and weakens the association between openness, relationship satisfaction, and topic avoidance. Using data from 334 individuals in romantic relationships, results revealed that perceived partner unresponsiveness was positively associated with State of the Relationship, relationship satisfaction was positively associated with Conflict-Inducing and Negative Life Experiences, such that as scores on relationship satisfaction and perceived partner unresponsiveness increased, topic avoidance scores also increased. Openness was not associated with Topic Avoidance. Additionally, as predicted, dogmatism moderated the association between relationship satisfaction and State of the Relationship Topic Avoidance, the associations between perceived partner unresponsiveness and State of the Relationship Topic Avoidance and Negative Life Experiences Topic Avoidance. This research has important implications for clinicians working with individuals who present with relational concerns
and exhibit dogmatic behavior. Limitations and future directions are discussed.
and exhibit dogmatic behavior. Limitations and future directions are discussed.
ContributorsMikel, Lindsay (Author) / Randall, Ashley K. (Thesis advisor) / Bludworth, James (Committee member) / Guerrero, Laura (Committee member) / Arizona State University (Publisher)
Created2019
Description
Stress in romantic relationships is an all-too-common phenomenon that has detrimental effects on relationship well-being. Specifically, stress can increase partners’ negative interactions, ultimately decreasing effective communication and overall relationship functioning. Positive dyadic coping (DC) occurs when one partner assists the other in coping with stress (e.g. empathizing or helping the partner problem-solve solutions to their stress), and has been proposed as a method of buffering the deleterious effect of stress on interaction quality. One possible mechanism between the positive associations between DC and interaction quality could be how partners verbally express their support (e.g., more we-talk) during discussions about external stress. Using real-time interaction data from 40 heterosexual couples, this project examined whether observed positive and negative DC was associated with greater (or lesser) levels of perceived interaction quality. Further, language use (i.e., pronouns, emotion words, cognition words) was assessed as mediators in the associations between DC and interaction quality. Overall, results suggested that language did not mediate the effect of DC on interaction quality; however, there were several interesting links between DC, language, and interaction quality. Implications of these findings for relationship researchers and mental health clinicians working with couples are discussed.
ContributorsLau, Kin Hang (Author) / Randall, Ashley K. (Thesis advisor) / Duran, Nicholas (Committee member) / Pereira, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017