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Adele Easy On Me Twitter Sentiment
Social Media and Posts
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Free
About
Focused on the viral reception of Adele's "Easy On Me", this collection contains tweet data harvested using the
rtweet package on the day of the single's release. It provides a granular look at fan interactions, sentiment, and the global buzz surrounding the artist's return. The data is particularly significant for understanding the dynamics of music releases in the social media age, allowing researchers to explore how "comeback" narratives drive engagement and how specific topics emerge within the fan community immediately following a launch.Columns
- user_id: The unique identifier associated with the user who posted the tweet.
- status_id: The unique identifier for the specific tweet or status update.
- created_at: The timestamp indicating the exact date and time the tweet was published.
- screen_name: The display handle of the user who posted the content.
- text: The raw text content of the tweet, including the hashtag #EasyOnMe.
- source: The device or platform application used to publish the tweet (e.g., Twitter for iPhone, Twitter for Android).
- display_text_width: The length of the tweet content in characters.
- favorite_count: The number of likes the tweet had received at the moment of data collection.
- retweet_count: The number of times the tweet had been retweeted at the moment of data collection.
- hashtags: A list of hashtags included within the tweet text.
- status_url: The direct URL link to the specific tweet.
Distribution
The data is organised into tabular CSV format. The primary file,
twts_tweets.csv, is approximately 5.23 MB in size and contains exactly 18,000 records, representing the maximum cap for the free account used for collection at the time. The dataset was originally split into two files to separate tweet content from user metadata (twts_users), which can be rejoined using the user_id column.Usage
- Sentiment Analysis: Assess the emotional tone (positive, negative, neutral) of the public reaction to the new single.
- Topic Modelling: Identify prevailing themes and discussions occurring alongside the release hashtag.
- Exploratory Data Analysis (EDA): Practise data cleaning and visualisation techniques on real-world unstructured text data.
- Social Trend Analysis: Examine how engagement metrics (likes, retweets) correlate with tweet length or platform source.
- Platform Usage Study: Compare the distribution of tweets sent from different devices (iPhone vs. Android).
Coverage
- Time Range: The data covers the immediate 24-hour period of 15 October 2021, the day of the single's release.
- Geographic Scope: Global, reflecting the worldwide user base of Twitter, though restricted to tweets containing the specific hashtag.
- Demographic Scope: Twitter users participating in the #EasyOnMe conversation.
- Note: The collection is capped at 18,000 tweets; therefore, it represents a sample of the total conversation rather than the entirety of all tweets posted that day.
License
CC0: Public Domain
Who Can Use It
- Data Science Students: Ideal for those learning R or Python for text mining and Natural Language Processing (NLP).
- Music Industry Analysts: Useful for gauging the immediate impact of major artist releases on social platforms.
- Social Media Researchers: Relevant for studying fan behaviour and the mechanics of viral trends.
Dataset Name Suggestions
- Adele Easy On Me Twitter Sentiment
- Easy On Me Release Day Tweets
- Adele 2021 Comeback Social Reaction
- Hashtag EasyOnMe Dataset 15 Oct 2021
Attributes
Original Data Source: Adele Easy On Me Twitter Sentiment
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