  Social media has transformed the advertising landscape, becoming an essential
tool for reaching and connecting with consumers. Its sharing and engagement
features amplify brand exposure, while its cost-effective options provide
businesses with flexible advertising solutions. TikTok is a more recent social
media platform that has gained popularity for advertising, particularly in the
realm of e-commerce, due to its large user base and viral nature. TikTok had
1.2 billion monthly active users in Q4 2021, generating an estimated $4.6
billion revenue in 2021. Virality can lead to a massive increase in brand
exposure, reaching a vast audience that may not have been accessible through
traditional marketing efforts alone. Advertisements for technological products
are an example of such viral ads that are abundant on TikTok. The goal of this
thesis is to understand how creators, community activity, and the
recommendation algorithm influence the virality of advertisements for
technology products on TikTok. The study analyzes various aspects of virality,
including sentiment analysis, content characteristics, and the role of
influencers. It employs data scraping and natural language processing tools to
analyze metadata from 2,000 TikTok posts and 274,651, offering insights into
the nuances of viral tech product advertising on TikTok.
