YouTube Trending Videos Dataset

Exploring YouTube Trending Videos

By dskl [source]

About this dataset

> > Moreover it also reveals various engagement metrics such as the number of views the video has received, likes and dislikes it has garnered from viewership. Additionally information related to comment count on particular videos enables analysis regarding viewer interaction and response. Furthermore this dataset describes whether comments or ratings are disabled for a particular video allowing examination into how these factors impact engagement. > > By exploring this dataset in-depth marketers can gain valuable insights into identifying trends in content popularity across different countries while taking into account timing considerations based on published day of week. It also opens up avenues for analyzing public sentiment towards specific videos based on likes vs dislikes ratios and comment count which further aids in devising suitable marketing strategies. > > > Overall,this informative dataset serves as an invaluable asset for researchers,data analysts,and marketers alike who strive to gain deeper understanding about trending video patterns,relevant metrics influencing content virality,factors dictating viewer sentiments,and exploring new possibilities within digital marketing space leveraging YouTube's wide reach

How to use the dataset

> # How to Use This Dataset: A Guide > > > In this guide, we will walk you through the different columns in the dataset and provide insights on how you can explore the popularity and engagement of these trending videos. Let's dive in! > > ## Column Descriptions: > > - title: The title of the video. > - channel_title: The title of the YouTube channel that published the video. > - publish_date: The date when the video was published on YouTube. > - time_frame: The duration of time (e.g., 1 day, 6 hours) that the video has been trending on YouTube. > - published_day_of_week: The day of week (e.g., Monday) when the video was published. > - publish_country: The country where the video was published. > - tags: The tags or keywords associated with the video. > - views: The number of views received by a particular video > - likes: Number o likes received per each videos > - dislike: Number dislikes receives per an individual vidoe > 11.comment_count: number of comments > > > ## Popular Video Insights: > > To gain insights into popular videos based on this dataset, you can focus your analysis using these columns: > > title, channel_title, publish_date, time_frame, and** publish_country**. > > By analyzing these attributes together with other engagement metrics such as views ,likes,**dislikes,**comments),comment_count you can identify trends in what type content is most popular both globally or within specific countries. > > > For instance: > - You could analyze which channels are consistently publishing trending videos > - Explore whether certain types of titles or tags are more likely to attract views and engagement. > - Determine if certain days of the week or time frames have a higher likelihood of trending videos being published. > > ## Engagement Insights: > > To explore user engagement with the trending videos, you can focus your analysis on these columns: > > likes, dislikes, comment_count > > By analyzing these attributes you can get insights into how users are interacting with the content. For example: > - You could compare the like and dislike ratios to identify positively received videos versus those that are more controversial. > - Analyze comment counts to understand how users are engaging with the content and whether comments being disabled affects overall

Research Ideas

> - Analyzing the popularity and engagement of trending videos: By analyzing the number of views, likes, dislikes, and comments, we can understand which types of videos are popular among YouTube users. We can also examine factors such as comment count and ratings disabled to see how viewers engage with trending videos. > - Understanding video trends across different countries: By examining the publish country column, we can compare the popularity of trending videos in different countries. This can help content creators or marketers understand regional preferences and tailor their content strategy accordingly. > - Studying the impact of video attributes on engagement: By exploring the relationship between video attributes (such as title, tags, publish day) and engagement metrics (views, likes), we can identify patterns or trends that influence a video's success on YouTube. This information can be valuable for content creators looking to optimize their titles or tags to increase visibility and engagement with their videos

Acknowledgements

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

License

> > > See the dataset description for more information.

Columns

File: youtube.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 dskl.