Social Media Engagement Levels For YouTube Tweets
Analyzing Likes, Retweets, and Conversations
@kaggle.thedevastator_social_media_engagement_levels_for_youtube_tweet
Analyzing Likes, Retweets, and Conversations
@kaggle.thedevastator_social_media_engagement_levels_for_youtube_tweet
By Twitter [source]
This dataset offers an exciting opportunity to explore how YouTube tweets and videos influence social media engagement. Through a comprehensive examination of likes, retweets, and quote counts across various topics or categories of videos, researchers can gain valuable insight into users’ reactions to content from popular YouTube channels. By collecting data on the level of conversations, this dataset will enable researchers to measure the success of YouTube's marketing efforts – along with those of its competitors – in driving viewer engagement. Further research could reveal patterns related to the demographic makeup of viewers across age groups and locations that have higher levels of conversation when responding to posted tweets. Investigating these patterns could be crucial in creating more effective strategies for interacting with potential consumers on social media platforms
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How to Use this Dataset
Analyze Conversation Patterns – Researchers can utilize the tweets and conversation metrics in this dataset to analyze the different conversation patterns related to each topic or video category discussed on YouTube. This includes topics such as politics, sports, music, and more. Through analyzing these conversations, researchers can gain an understanding of what drives engagement with YouTube videos and how they may be used as a platform for further marketing campaigns.
Measure Engagement Levels – This dataset contains metrics that allow users to measure overall engagement levels for different topics of Twitter conversations in relation to YouTube content. By studying these metrics, researchers are able to compare the level of engagement that different types of content receive on various social media platforms such as Twitter.
Assess Marketing Strategies Effectiveness –Researchers can use this data set to assess how effective various marketing strategies are by looking at like counts, retweet counts and quote counts for particular campaigns or categories of YouTube contents . In addition , research could be conducted on specific marketing campaigns in areas where companies wish optimize their success rates such as increasing clicks or viewer retention rates .
Compare Engagement Across Platforms-The data contained within this dataset allows users compare engagement levels across other social media channels such as Facebook and Instagram in order learn which ones drive higher levels of engagement when it comes promoting content on YouTube or creating conversations around certain topics
Studying the correlation between YouTube content categories and levels of engagement, in order to identify which types of videos/topics have higher engagement rates.
Assessing patterns in likes, retweets and conversations in response to different topics or categories of videos related to YouTube content, in order to gain an understanding of the type of content that typically receives the most conversation.
Tracking changes in engagement levels over time for different topics or channels on YouTube, such as popular channels or videos with high view counts, in order to measure the overall effectiveness of YouTube's marketing campaigns across social media platforms
If you use this dataset in your research, please credit the original authors.
Data SourceLicense
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.
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Twitter.
CREATE TABLE youtube (
"content" VARCHAR,
"created_at" VARCHAR,
"date" VARCHAR,
"likecount" BIGINT,
"media" VARCHAR,
"outlinks" VARCHAR,
"quotecount" BIGINT,
"quotedtweet" VARCHAR,
"replycount" BIGINT,
"retweetcount" BIGINT,
"retweetedtweet" VARCHAR,
"url" VARCHAR,
"id" BIGINT,
"conversationid" BIGINT
);
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