Barbie
-Ken's Nomination

An social media data analysis across gender, film, and culture.

The Topic

We aimed to analyze X (Twitter) engagement regarding Ryan Gosling's nomination by influence, location, gender, and cross-culture norms.

My role

Served as project manager and researcher.

The Approach

The Full Story

1. Decide RQs & Manual Coding

RQ -

RQ1: How do the different geographical locations influence users’ gender perspectives towards Gosling’s nomination for Ken in the movie ‘Barbie’?

RQ2: How do geographic locations and its associated cultural norms (Individualism vs. Collectivism) influence public perception and discussion of Ryan Gosling's nomination of Ken in the ‘Barbie’ Movie?

RQ3 : Does the engagement level (reach, likes, retweets) of tweets about Gosling’s Oscar nomination correlate with the sentiment expressed in the tweets?

We utilized Meltwater to filter 10k tweets related to the topic and the first 1000 was manually coded with our pre-defined requirements, such as whether the post contain negative emotions.

Result - We found that public perceptions of Ryan Gosling’s Oscar nomination for “Barbie” were not heavily influenced by geographic or cultural factors in North America or Asia. Among 1,000 analyzed tweets, individualistic perspectives dominated, with 76.8% from Asian users and 65.4% from North American users. Additionally, tweets with negative sentiments had higher engagement levels.

2. Utilize R & SPSS for advanced analysis

Method & Packages Used:

Text Mining
Wordcloud
Syuzhet
Multinomial Regression

Results - The study shows that geographic location does not significantly affect how gender perspectives are expressed regarding Gosling’s nomination, which contrasts with our initial findings. However, cultural norms and geography do influence public sentiment, with collectivism linked to more negative and fewer neutral sentiments. Female perspectives show distinct sentiment toward the movie and nomination. Similar to our preliminary result, tweets with negative sentiments still indicates a trend to attract higher engagement.

Recommendations for the Industry -