TheEllenShow's Tweets
Exploring Influencer Impact and Reach on Social Media
By Twitter [source]
About this dataset
This dataset contains powerful insights into the influential voice of TheEllenShow on Twitter. It records tweets from the popular profile and gives an in-depth look at the level of engagement and reach each post had. With 12 columns that capture various metrics such as content, creation time, number of likes and retweets received, researchers can analyse how much influence their messages have on their audience. The data visualisations provides a unique opportunity to examine which posts garnered the most attention — allowing us to measure what resonates with people while also acknowledging other users by quoted tweets count. This dataset provides a great way to explore how social media content is impacting our lives — understanding how we impact each other through digital communication more than ever before!
More Datasets
For more datasets, click here.
Featured Notebooks
- 🚨 Your notebook can be here! 🚨!
How to use the dataset
This dataset contains tweets from TheEllenShow, a popular Twitter profile. This dataset provides valuable information regarding the reach and resonance of all their associated posts. It consists of 12 columns that outline different metrics such as the content, when it was created, likes and retweets received along with other data. With this data at hand, researchers can measure how much engagement each post has had and assess the influence they have on their audience.
Research Ideas
- Identifying Top Performing Post Types: By analysing the tweet content, users can determine which types of posts get the most engagement in terms of likes and retweets. This information could be used to adjust content strategy for maximum impact.
- Examining Spikes in Engagement: Researchers can use this data to measure when tweets lead to especially high levels of engagement from followers - useful for understanding what type of items create a surge in responses from their online audience.
- Predictive Modeling: Using machine learning algorithms, one can develop predictive models that can help find patterns and correlations between different tweet attributes and the response they generate (likes/retweets). Those insights could then be leveraged to determine which types of posts are most likely to generate a larger response rate amongst followers, helping inform future content strategies
Acknowledgements
If you use this dataset in your research, please credit the original authors.
Data Source
License
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
Acknowledgements
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Twitter.