Viral/Heboh News (Twitter)

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Viral/Heboh News (Twitter)

Analyzing Popularity of Online Engagement

By [source]

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About this dataset

This dataset gives us an intriguing insight into the power of online news engagement. Ten popular news portals have been tracked using Twitter data, including viral or heboh tweets and the date/time, number of retweets, and username. This is an excellent tool for determining how people perceive different types of information as it relates to online platforms. It can also be used to understand how quickly topics become trending or popular on social media platforms like Twitter. Data from this dataset can be used to evaluate the overall impact a single tweet or topic has on the internet, providing valuable knowledge for understanding marketing strategies and successful digital communication tactics

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How to use the dataset

How to Use This Dataset

This dataset provides an interesting opportunity to analyze the popularity of online news engagement by looking at tweets from 10 official news portal accounts on Twitter containing the words Viral or Heboh. The dataset includes five columns that track each account's tweet, date/time, number of retweets, and username. By following this guide you can make use of this data for your own research purposes.

• Set a research question: Before using the data it is important to set a research question that you want to answer by working with this data. This will allow you to focus your analysis and ensure that you are utilizing the most relevant parts of the dataset for your purposes.
• Get acquainted with column values: The five columns in this dataset are ‘Tweet’, ‘Tanggal’, ‘Jumlah Retweet', 'Username'. In order to work effectively with this dataset it is helpful to gain a better understanding of what information each field contains and if there are any limitations present in the values they contain (i.e empty fields).
• Data cleaning & transformation: Once familiarized with what columns provide us with useful insights we can clean up our data by removing duplicates/missing values etc and transform them as needed such as converting dates into numerical form in order to more easily compare different points in time etc..
• Analysis & Visualization: After having identified our research questions and making sure all data is prepared for analysis we can begin exploring our findings either through statistical tests or visualisations depending on what best suits one's purpose!

By taking these steps you will be able to develop an effective approach when working with this challenging dataset!

Research Ideas

• Generating reports to track how quickly content from the news portals spreads on Twitter and identifying the most effective tweets.
• Identifying trends in online engagements for each news portal and find opportunities to optimize content engagement.
• Examining sentiment around particular topics, allowing us to better understand public opinion of Viral or Heboh news stories on Twitter

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

File: viralheboh.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .