GoldGloveTV Tweets

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GoldGloveTV Tweets Sentiment Analysis

Measuring Engagement and Popularity

By Twitter [source]

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About this dataset

This dataset contains sentiment analysis and information on the tweets of GoldGloveTV, one of the most popular gaming Twitch streamers. It includes data such as timestamp, content of the tweet, number of likes and replies, retweet count, URL associated with each tweet, conversation id associated to the given tweet and various other metadata. This dataset offers invaluable insights about the engagement and popularity surrounding GoldGloveTV's tweets. Furthermore, precise analytical operations concerning different aspects can be performed using this data in order to understand user behaviour better. This is a valuable resource for identifying successful strategies employed by GoldGloveTV in terms of marketing his brand or understanding how users engage with his content on this social media platform

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How to use the dataset

1. Exploring the descriptor data: The first step to analyzing this dataset is to explore the descriptive information such as the tweet timestamp, text, likes, reply count and retweet count among others. This will enable you to look at the trend of GoldGloveTV’s engagement and gain an idea of their most popular posts.

2. Analyze sentiment: Another useful way to use this dataset is to analyze sentiment by looking at each individual tweets' polarities (positive/negative) or subjectivity (objective/subjective). This could provide valuable insight on what topics people are generally interested in or enthusiastic about when discussing GoldGloveTV on Twitter.

3. Compare conversations: You can also compare conversations between different tweets with same conversation id if you want a bigger picture of how people are discussing about specific topics related to GoldGloveTV. Additionally, you can use the URL data in order check out any videos that were released alongside certain Tweets for more context (if needed).

4. Visualizing results: Finally, once you have gained all the necessary insights from analysing this data then it's important to visualize them using charts like scatter plots or bar graphs so that it's easier for anyone else looking into your analysis can understand your findings easily and quickly based on what they see in these visuals rather than having them guess through your raw numbers

Research Ideas

• Analyzing the trends of customer feedback over time to determine the sentiment associated with a particular brand or product. This can be used to help companies adjust their promotional strategies and improve their customer experience.

• Use sentiment analysis on Twitter comments related to specific topics could be helpful for creating market research and gathering insights from user feedback.

• Analyzing the sentiment around different hashtags in order to track conversations about current events, products, services, and brands in real-time and measure how people are responding to them

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.

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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.