YouTube Crisis Actor Videos And Recommendations

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YouTube Crisis Actor Videos and Recommendations

Dataset of Crisis Actor Videos on YouTube and their Recommendations

By Jonathan A. [source]

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About this dataset

This dataset provides valuable insights into crisis actor videos and their corresponding recommendations on YouTube. It consists of a total of 8823 videos, accounting for an astounding 3,956,454,363 views. These videos were retrieved from YouTube's API and cover various categories and topics.

Specifically, this dataset focuses on crisis actor videos related to mass shootings, false flags, and other conspiracy theories that comprise around 20% of the collection. The remaining 80% explores conspiracies revolving around history, government institutions, and religions.

The dataset includes essential information such as the name and channel of the video uploader. Additionally, it provides details about viewer engagement through likes and dislikes counts. Furthermore, each video is assigned a category or topic to facilitate analysis.

It is important to note that approximately 100 music videos were excluded from the initial data set to maintain relevance to crisis actors.

Overall, this project aims to shed light on the prevalent issue of crisis actors on YouTube by providing researchers with a comprehensive dataset for further exploration and analysis. This highly informative dataset serves as a valuable resource for investigating trends within crisis actor content while contributing towards raising public awareness surrounding this topic

How to use the dataset

• Understanding the Dataset:

The dataset comprises several columns that provide specific information about each video and its corresponding recommendations. Here's a brief overview of the key columns:

• name: The title or name of the YouTube video.

• channel: The name of the YouTube channel that uploaded the video.

• category: The category or topic of the video.

• views: The number of views the video has received.

• likes: The number of likes received by each video.

• dislikes: The number of dislikes received by each video.

• Exploring Categories:

One way to analyze this dataset is by examining different categories mentioned in each video entry. This could involve identifying patterns within categories or comparing engagement metrics (views, likes, dislikes) across various topics.

For example, you might want to investigate how crisis actor videos are categorized compared to other conspiracy-related videos present in this dataset.

• Analyzing Engagement Metrics:

To gain insights into users' response towards different videos related to crisis actors or conspiracy theories, it is recommended that you examine engagement metrics such as views, likes, and dislikes.

You can compare these metrics between individual videos within specific categories or observe trends across all entries.

• Investigating Popularity:

Understanding which channels have maximum viewership within this particular subject area can offer valuable information for further analysis.

Examining which channels have consistently high views or engagement metrics (likes/dislikes) can help identify influential content creators related to crisis actors or conspiracy theories.

• Identifying Recommendations:

The dataset also provides information about the recommendations associated with each video entry. By analyzing these recommendations, you can gain insights into the video content YouTube suggests to users who view crisis actor videos.

You could focus on specific keywords within recommendation titles or explore patterns in terms of topic relevance or common recommendations across multiple entries.

• Cross-Referencing External Information:

As this dataset does not provide detailed descriptions or context for each video, it is advisable to cross-reference external sources to gather additional information if needed.

By using the provided video titles and channel names, you can search for more details about specific videos

Research Ideas

• Analyzing the correlation between likes, dislikes, and views: This dataset can be used to analyze the relationship between the number of likes and dislikes a video receives and its overall views. By examining this relationship, one could gain insights into factors that contribute to increased engagement or disinterest in crisis actor videos.
• Identifying popular YouTube channels in the crisis actor category: By analyzing the dataset, one can identify which YouTube channels have uploaded the most crisis actor videos and have gained high viewership. This information can provide insights into key influencers in this category and their impact on audience engagement.
• Understanding user preferences in related videos: The dataset includes recommendations for each video, which can be used to analyze user preferences for crisis actor content. By examining patterns in recommended videos for specific categories or titles, researchers can gain an understanding of viewer interests and tailor their content accordingly

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: YouTube Crisis Actor Video List_Cut_2_24_18 - Youtube_Crisis_actor_nodes_only.gexf.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 Jonathan A..