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Twitter Mobile Tech Trends Dataset
Social Media and Posts
Tags and Keywords
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Free
About
Explore over a decade of conversations about mobile phones with this collection of tweets spanning from 2010 to 2021. This data offers a unique opportunity to analyse and capture trends, public sentiment, and discussions surrounding mobile technology on Twitter over the past decade. It is a valuable resource for understanding the evolution of mobile phone discourse in online communities.
Columns
- ID: A numerical identifier for each tweet.
- phone name: The name of the mobile phone model mentioned in the tweet.
- date: The date and time when the tweet was posted.
- username: The Twitter username of the account that posted the tweet.
- tweet: The full text content of the tweet.
- language: The language of the tweet, which is English ('en') for all entries.
- replies_count: The total number of replies the tweet received.
- retweets_count: The total number of times the tweet was retweeted.
- likes_count: The total number of likes the tweet received.
- hashtags: A list of hashtags included in the tweet.
- link: A direct URL to the original tweet on Twitter.
Distribution
The data is provided in a single CSV file named
phone_tweets.csv, with a size of 15.87 MB. The dataset contains approximately 62,600 rows and 11 columns.Usage
This data is ideal for sentiment analysis, trend analysis, market research, and natural language processing tasks. Researchers can track the popularity of different phone brands and models over time, analyse marketing campaign effectiveness, and understand public reaction to new technology releases.
Coverage
- Geographic: The geographic origin of the tweets is not specified.
- Time Range: The dataset includes tweets posted between 13 January 2010 and 9 November 2021.
- Demographic: The data consists of tweets from a wide variety of public Twitter users who posted in English about mobile phones.
License
CC0: Public Domain
Who Can Use It
- Market Researchers: To analyse consumer preferences and track brand popularity over time.
- Data Scientists: For building models to predict technology trends or perform sentiment analysis.
- Social Media Analysts: To study online conversations and community engagement related to mobile technology.
- Academics: To research the evolution of language and communication on social networks.
Dataset Name Suggestions
- A Decade of Mobile Phone Tweets (2010-2021)
- Mobile Phone Twitter Mentions Archive
- Twitter Mobile Tech Trends Dataset
- Public Opinion on Phones: A Twitter Analysis
Attributes
Original Data Source: Twitter Mobile Tech Trends Dataset
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