Business Commons^™

The Impact Of Social Media Account Types On Travel Intention, Nuri Seo

Theses and Dissertations

The purpose of this research is to explore and understand how social media account types (DMOs, friends, and other individuals) influence traveler destination perceptions (destination trust and destination attractiveness) and visit intention. The current study also investigates the impact of the likes option on social media account types, which influence traveler perceptions and visit intention. Previous research had not explored three social media account types: DMOs, friends, and individuals based on Source Credibility Theory and the impact of likes on traveler destination perceptions and visit intention. The experimental design was used to test the research model; an experiment with a …

Analyzing Twitter Usage Differences Between Student Season Ticket Buyers And Non-Buyers, Matthew Aloysius Kinney

Theses and Dissertations

This thesis investigates the importance of social media to college students as it relates to purchasing game tickets. More specifically, the thesis examines the role that Twitter and marketing play in purchase intentions of students that actually purchase tickets. The results demonstrate that those who have purchased a ticket membership package are more likely to follow said organization on Twitter. Results also found that no significant difference exists in Twitter Intensity based on whether or not a student has purchased a ticket membership package.

Three Research Essays On Human Behaviors In Social Media, Jiao Wu

Theses and Dissertations

Social Media (SM) has grown to be one of the most popular Internet technologies for individual users and has fostered a global community. For instance, recent statistics reveal that monthly active users of Facebook are almost 1.5 billion by Mar 2015. At the same time, 20% of internet users in the US are expected to have Twitter accounts. This figure has grown from 15.2% in 2012, and is expected to rise to 24.2% by 2018 (Twitter 2015).

People like spending their time on SM to track the latest news, seek knowledge, update personal status, and connect with friends. It is …

Three Essays On Retransmission Of Brand Messages In Social Media, Nima Yahyapour Jalali

Theses and Dissertations

Social networks have emerged as an important channel for brands to communicate with customers both directly as well as secondarily through customers who share the communications with others. A value of this channel to brands, therefore, depends on how effective they are in increasing the retransmission of their messages by customers. This is the issue that we investigate through three essays using the social media site Twitter as our research setting. Our investigation is based on the theory that retweeting is a choice made by consumers who rely on constructive preferences (Bettman, Luce and Payne 1998) while seeking three intangible …

Why Do People Give? Similarity Based Persuasion On Charitable Appeals And Self-Presentation On Social Media, Jihye Lee

Theses and Dissertations

Despite the sizable donations and the variety of views to research an individual's charitable motivations, the individual's charitable giving has remained somewhat stagnant. Ever since the economic crisis of 2008, contributions to charities have decreased. Therefore, garnering donations is a significant challenge for charitable organizations. Moreover, for individuals who have decided to make voluntary contributions, determining which of the over 800,000 nonprofit organizations to contribute to can be a challenging task, as well. The question of how nonprofit organizations should foster awareness and receive donations is of critical importance, yet the answer is not quite clear. In the current fierce …

Three Essays On Opinion Mining Of Social Media Texts, Shuyuan Deng

Theses and Dissertations

This dissertation research is a collection of three essays on opinion mining of social media texts. I explore different theoretical and methodological perspectives in this inquiry. The first essay focuses on improving lexicon-based sentiment classification. I propose a method to automatically generate a sentiment lexicon that incorporates knowledge from both the language domain and the content domain. This method learns word associations from a large unannotated corpus. These associations are used to identify new sentiment words. Using a Twitter data set containing 743,069 tweets related to the stock market, I show that the sentiment lexicons generated using the proposed method …