Social Media Productivity Loss Data

Columns

• UserID: A unique identifier assigned to each user.
• Age: The user's age, typically ranging from 18 to 64, with an average of 41.
• Gender: The user's gender, including male (51%), female (32%), and non-binary options.
• Location: The geographic location of the user, with significant representation from India (23%) and the United States (17%).
• Income: The user's income level, generally between £20,100 and £99,700, with an average of £59,500.
• Debt: A boolean indicator of whether the user has debt (60% true, 40% false).
• Owns Property: A boolean indicator of whether the user owns property (54% true, 46% false).
• Profession: The user's occupation or job, with common categories including Students (25%) and Waiting staff (19%).
• Demographics: Statistical data about the user, such as age, gender, and income, categorised as Rural (75%) or Urban (25%).
• Platform: The specific social media platform the user is engaging with, such as TikTok (27%) or Instagram (26%).
• Total Time Spent: The total time, in units not specified, the user spends on the platform, averaging 151 units.
• Number of Sessions: The total number of times the user has logged into the platform, averaging 10 sessions.
• Video ID: A unique identifier for a video, spanning a wide range of values.
• Video Category: The category or genre of the video, with Jokes/Memes (18%) and Life Hacks (16%) being common.
• Video Length: The duration of the video, averaging 15.2 units.
• Engagement: User interaction with the video, such as likes, comments, and shares, with an average engagement score of 5,000.
• Importance Score: A score indicating the perceived importance of the video to the user, on a scale of 1 to 9, averaging 5.13.
• Time Spent On Video: The amount of time, in units not specified, the user spends watching a video, averaging 15 units.
• Number of Videos Watched: The total number of videos watched by the user, averaging 25.2.
• Scroll Rate: The rate at which the user scrolls through content, averaging 49.8.
• Frequency: How often the user engages with the platform, categorised by time of day (Evening 37%, Night 31%).
• Productivity Loss: The impact of platform usage on the user's productivity, scored on a scale of 1 to 9, averaging 5.14.
• Satisfaction: The user's satisfaction level with the platform or content, on a scale of 1 to 9, averaging 4.86.
• Watch Reason: The primary reason why the user is watching a video, such as Habit (34%) or Boredom (28%).
• Device Type: The type of device the user is using, predominantly Smartphone (59%) or Tablet (28%).
• OS: The operating system of the user's device, with Android (50%) and iOS (26%) being the most frequent.
• Watch Time: The time of day when the user watches videos, with data primarily from 29th July 2024 to 30th July 2024.
• Self Control: The user's ability to control their usage of the platform, rated on a scale of 3 to 10, averaging 7.09.
• Addiction Level: The user's level of dependency on the platform, on a scale of 0 to 7, averaging 2.91.
• Current Activity: What the user is doing while watching the video, such as "At home" (38%) or "At school" (27%).
• Connection Type: The type of internet connection the user has, primarily Mobile Data (69%) or Wi-Fi (31%).

Distribution

Usage

• Conducting research into social media behaviour and user psychology.
• Analysing the effects of social media on time management and productivity.
• Developing strategies for digital well-being and mitigating productivity loss.
• Understanding user engagement patterns with different platforms and content types.
• Informing marketing campaigns by identifying key user demographics and usage habits.
• Exploring the correlation between social media use, self-control, and addiction levels.
• Studying content consumption preferences, such as video categories and watch reasons.

Coverage

License

Who Can Use It

• Researchers: To investigate social media addiction, digital distraction, and user behaviour patterns.
• Marketers and Advertisers: To better understand target audiences, consumption habits, and effective platform engagement strategies.
• Social Scientists and Psychologists: To study the societal impact of social networks, self-control, and satisfaction levels among users.
• Data Analysts: For extracting trends in user demographics, platform usage, and content interaction for various studies.
• Developers and Platform Designers: To optimise user experience, content delivery, and features based on device types, operating systems, and connection preferences.
• Educators and Policy Makers: To inform educational programmes or public health initiatives related to responsible social media use and productivity.

Dataset Name Suggestions

• Social Media Productivity Loss Data
• User Engagement on Digital Platforms
• Online Time Management Dataset
• Social Network Behaviour Analytics
• Digital Lifestyle Impact Data

Attributes