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Social media has not always been a traditional form of business strategy for the fashion industry, therefore a study on the role of social media on user engagement for different tiers of fashion brands was conducted. A combination of multiple regression models, ANOVA analysis, and hashtag analysis was done to

Social media has not always been a traditional form of business strategy for the fashion industry, therefore a study on the role of social media on user engagement for different tiers of fashion brands was conducted. A combination of multiple regression models, ANOVA analysis, and hashtag analysis was done to understand various aspects of the research question. Tests were run against different post types to gain deeper insights on engagement levels and statistical significance. Post frequency and correlation analysis was conducted to understand how followers respond to the content. Overall, reels and carousel media were the most successful in increasing and maintaining user engagement. Prada has the most inactive users and ineffective social media strategies to increase engagement. While they have a high following they are unable to sustain engagement levels through their posts. Whereas, Teddy Fresh, despite being a smaller brand has been successful in maintaining engagement levels through their niche target market. Lastly, SKIMS has the fastest growth rate and has been able to increase following through their high frequency post schedule. For each of the brands, this information can be used to further strategize the marketing content. Social media is dynamic and therefore the approach for curating content will differ; being able to understand which types of posts are doing well is helpful for the brands as they can continue to run analysis when needed.

ContributorsLe, Devonne (Author) / Jasti, Viveka (Co-author) / Sopha, Matthew (Thesis director) / Sirugudi, Kumar (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2023-05
Description
Misinformation, defined as incorrect or misleading information, has been around since the beginning of time. However, the rise of technology and widespread use of social media has allowed misinformation to evolve and gain more traction. This study aims to examine health and political misinformation within the contexts of the COVID-19

Misinformation, defined as incorrect or misleading information, has been around since the beginning of time. However, the rise of technology and widespread use of social media has allowed misinformation to evolve and gain more traction. This study aims to examine health and political misinformation within the contexts of the COVID-19 pandemic and the 2020 U.S. Presidential Election. Utilizing samples of misinformation from the 45th president of the United States, I analyzed the levels of engagement that this misinformation received on the social media platform X, formerly known as Twitter. I also examined how various Google search query trends changed over time in response to this misinformation. Then, I categorized the data into misleading statistics, misrepresentations of opinions as facts, or completely false content. Lastly, I looked into the physical responses that resulted from the spread of such misinformation. My findings of this case study showed that misinformation received significantly more attention than other social media posts, as evidenced by increased Google searches related to the topics and higher levels of likes and retweets on misinformative Tweets during the specified periods. Furthermore, the former president employed all three types of misinformation, with misleading statistics most prevalent in the health misinformation sample and misrepresentations of opinions as facts most prevalent in the political misinformation sample. The repercussions of this misinformation encompassed individuals ingesting unsafe products, decreased trust in the electoral process, and a violent insurrection at the U.S. Capitol. Despite the existing research in this field, there remains much more to be uncovered regarding the vast amount of misinformation circulating on the Internet.
ContributorsShah, Sona (Author) / Boghrati, Reihane (Thesis director) / Simeone, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor)
Created2023-12
ContributorsShah, Sona (Author) / Boghrati, Reihane (Thesis director) / Simeone, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor)
Created2023-12
ContributorsShah, Sona (Author) / Boghrati, Reihane (Thesis director) / Simeone, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor)
Created2023-12