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UK/Global Cost of Living Social Discourse Data
Social Media and Posts
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About
This data product captures the intense public discourse surrounding the cost of living crisis, deemed a scorching topic during late summer 2022. It contains over 144,000 tweets composed in English, allowing for detailed analysis of public sentiment, key discussion points, and influencer activity related to economic pressures over a crucial three-week period. The records include not only the text of the message but also metadata detailing user engagement and account status.
Columns
The dataset comprises 12 distinct fields, providing both content and user metrics:
- date_time: The exact date and time when the message was published.
- username: The unique identifier for the user who sent the message.
- user_location: The location information provided by the user in their account settings, though this is not GPS generated.
- user_description: The text found in the user's 'about' section on their account.
- verified: A boolean value indicating whether the user possesses the 'verified by Twitter' blue tick.
- followers_count: The recorded number of followers an account had at the time the message was sent.
- following_count: The number of accounts followed by the user.
- tweet_like_count: The total number of likes accumulated by the message.
- tweet_retweet_count: The total number of retweets the message received.
- tweet_reply_count: The count of replies directed toward the message.
- source: Specifies the application or platform used to send the message (e.g., Twitter for iPhone, Twitter Web App).
- tweet_text: The actual text content included in the message.
Distribution
The data is delivered in a CSV file format titled
costofliving-query-tweets.csv, with a size of 65.56 MB. It contains more than 144,000 unique records. All messages are presented in the English language. This product is expected to be refreshed quarterly.Usage
The data is ideal for several applications, including:
- Social Monitoring: Tracking real-time social sentiment regarding economic policies and inflation.
- Natural Language Processing (NLP): Performing in-depth textual analysis and thematic modeling on public dialogue.
- Journalism and Policy Research: Identifying and analysing high-impact discussions and key opinion leaders related to the crisis.
- Platform Analysis: Studying user engagement patterns, such as reply and retweet rates, across different user demographics (e.g., verified versus non-verified accounts).
Coverage
The data covers messages published between 20 August 2022 and 9 September 2022. Geographically, the messages originate from various countries globally, although user location data is frequently missing (approximately 31% of records). Among the specific locations entered by users, London, England, represents the most common entry. All content is in English.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For developing models based on social media metrics like likes, retweets, and replies.
- Academics and Researchers: Those investigating the social and emotional impact of rising living costs, using the text and associated engagement metrics.
- Market Analysts: Individuals seeking insights into the language and concerns of consumers affected by economic downturns.
Dataset Name Suggestions
- Cost of Living Crisis Tweets: August-September 2022
- UK/Global Cost of Living Social Discourse Data
- 144k English Tweets on Socio-Economic Anxiety
Attributes
Original Data Source: UK/Global Cost of Living Social Discourse Data
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