Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

              Instagram’s Global Audience

              As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
              As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.

              Who is winning over the generations?

              Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.

The report provides a snapshot of the social media usage trends amongst online Canadian adults based on an online survey of 1500 participants. Canada continues to be one of the most connected countries in the world. An overwhelming majority of online Canadian adults (94%) have an account on at least one social media platform. However, the 2022 survey results show that the COVID-19 pandemic has ushered in some changes in how and where Canadians are spending their time on social media. Dominant platforms such as Facebook, messaging apps and YouTube are still on top but are losing ground to newer platforms such as TikTok and more niche platforms such as Reddit and Twitch.

This dataset captures insights from a survey on social media usage across diverse age groups and genders. It includes data on the most used platforms, daily screen time, reasons for usage, preferred content types, and how social media influences buying decisions. Additionally, it reflects users' concerns about privacy and their willingness to reduce usage. The dataset is useful for analyzing digital behavior, content preferences, and the social impact of online platforms. It can support research in marketing, psychology, and digital well-being, offering a snapshot of how people interact with and perceive social media in their daily lives.

Context: This dataset offers insights into the usage patterns of social media apps for 1,000 users across seven popular platforms: Facebook, Instagram, Twitter, Snapchat, TikTok, LinkedIn, and Pinterest. It tracks various metrics such as daily time spent on the app, number of posts made, likes received, and new followers gained.

Dataset Features:

User_ID: Unique identifier for each user. App: The social media platform being used. Daily_Minutes_Spent: Total time a user spends on the app each day, ranging from 5 to 500 minutes. Posts_Per_Day: Number of posts a user creates per day, ranging from 0 to 20. Likes_Per_Day: Total number of likes a user receives on their posts each day, ranging from 0 to 200. Follows_Per_Day: The number of new followers a user gains daily, ranging from 0 to 50. Context & Use Cases: This dataset could be particularly useful for social media analysts, digital marketers, or researchers interested in understanding user engagement trends across different platforms. It provides insights into how much time users spend, how actively they post, and the level of engagement they receive (in terms of likes and followers).

Conclusion & Outcome: Analyzing this dataset could yield several outcomes:

Engagement Patterns: Identifying which platforms have higher engagement in terms of time spent or likes received. Active Users: Determining which users are the most active across various platforms based on the number of posts and followers gained. User Retention: Studying the correlation between time spent and follower growth, providing insight into user retention strategies for different platforms. Overall, the dataset allows for exploration of social media usage trends and helps drive decision-making for marketing strategies, content creation, and platform engagement.

56.8% of the world’s total population is active on social media.

The results might surprise you when looking at internet users that are active on social media in each country.

Facebook and YouTube are still the most used social media platforms today.

This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools. The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011). The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels. References: Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4 Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. https://doi.org/10.1002/cpp.702 Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. https://doi.org/10.1016/S0005-7967(98)00034-5

Gen Z and Millennials are the biggest social media users of all age groups.

This dataset covers aspects of online politics in 25 democracies: 15 relatively old established European democracies (Austria, Belgium, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Sweden, Switzerland, United Kingdom); five non-European veteran democracies (Australia, Canada, Israel, Japan, New Zealand); two early (Portugal, Spain) and three late (Czech Republic, Hungary, Poland) third-wave (young) European democracies. The research population includes, in each country, parties that won 4% or more of the votes in two consecutive elections before April 2019 (a total of 141 parties and 145 leaders). The dataset includes external party level information such as performance in the last national elections, governmental status, party age, populism affiliation and leadership selection method. It also includes information related to the party leaders such as their term in leadership office and other formal positions. In addition it includes information about online activity mainly on the consumption (user related activities) of the parties and their leaders in Facebook and Twitter two of the most used social media platforms for political purposes.

The average person has 8-9 social media accounts. This has doubled since 2013, when the average person just had 4-5 accounts.

As of April 2024, Bahrain was the country with the highest Instagram audience reach with 95.6 percent. Kazakhstan also had a high Instagram audience penetration rate, with 90.8 percent of the population using the social network. In the United Arab Emirates, Turkey, and Brunei, the photo-sharing platform was used by more than 85 percent of each country's population.

📊 Social Media vs Productivity — Realistic Behavioral Dataset (30,000 Users)

This dataset explores how daily digital habits — including social media usage, screen time, and notification exposure — relate to individual productivity, stress, and well-being.

🔍 What’s Inside?

The dataset contains 30,000 real-world-style records simulating behavioral patterns of people with various jobs, social habits, and lifestyle choices. The goal is to understand how different digital behaviors correlate with perceived and actual productivity.

🧠 Why This Dataset is Valuable

• ✅ Designed for real-world ML workflows
  Includes missing values, noise, and outliers — ideal for practicing data cleaning and preprocessing.

• 🔗 High correlation between target features
  The perceived_productivity_score and actual_productivity_score are strongly correlated, making this dataset suitable for experiments in feature selection and multicollinearity.

• 🛠️ Feature Engineering playground
  Use this dataset to practice feature scaling, encoding, binning, interaction terms, and more.

• 🧪 Perfect for EDA, regression & classification
  You can model productivity, stress, or satisfaction based on behavior patterns and digital exposure.

🧾 Columns & Feature Info

📌 Notes

• Contains NaN values in critical columns (productivity, sleep, stress) for data imputation tasks
• Includes outliers in media usage, coffee intake, and notification count
• Target columns are strongly correlated for multicollinearity testing
• Multi-purpose: regression, classification, clustering, visualization

💡 Use Cases

• Exploratory Data Analysis (EDA)
• Feature engineering pipelines
• Machine learning model benchmarking
• Statistical hypothesis testing
• Burnout and mental health prediction projects

📥 Bonus

👉 Sample notebook coming soon with data cleaning, visualization, and productivity prediction!

Coding category:

Q1_Gender
1. Male 2. Female

Q2_Living_Area
1. Urban 2. Rural

Q3_Maritial_Status
1. No 2. Yes

SMAQ1 – SMAQ10
1. Never 2. Rarely 3. Sometimes 4. Often 5. Always

SMA_Scale_value

less than 20 to more than 40.

SMA_Scale (Class_Lebel) 1. Low addiction: Total score equal & less than 20 2. Moderate addiction: Total score in between 20 and 40 3. High addiction: Total score equal & greater than 40

This Dataset analyzed Social Media Addiction data from Daffodil International University (DIU) to classify their levels of Addiction into five categories: 1 (Never), 2 (Rarely), 3 (Sometimes), 4 (Often), and 5 (Always). The dataset used was included information on 1,030 participants from various Departments of DIU. The dataset contained 10 main attributes, comprising ten questions each for Social Media Addiction. The target SMA_Scale (Class_Lebel) was categorized as 1 (Low Addiction), 2 (Moderate Addiction), 3 (High Addiction). The distribution of instances for Class_Lebel was 728 (Low Addicted), 259 ((Moderate Addicted), 42 (High Addicted).

The cross-lingual natural disaster dataset includes public tweets collected using Twitter’s public API, filtering by location-related keywords and date, without using any additional filtering (e.g., we did not restrict the query to specific languages). We considered two disaster events and two long-term natural disasters across Europe (floods and wildfires) that received substantial news coverage internationally.

Three of the top languages were common to all the studied events: English (ISO 639-1 code: en), Spanish (es), and French (fr). Additionally, we found hundreds of messages for each event in other five languages, including Arabic (ar), German (de), Japanese (ja), Indonesian (id), Italian (it) and Portuguese (pt).

After collecting the data, we labelled tweets that contained potentially informative factual information. We name this group of tweets “informative messages.” Next, we used crowdsourcing to further categorize the messages into various informational categories. We asked three different workers to label each informative messages across languages. The target categories were based on an ontology from TREC-IS 2018, where we grouped some low level ontology categories into higher-level ones.

In this post, I'll give you all the social media addiction statistics you need to be aware of to moderate your social media use.

The state of Colorado currently lacks research that looks at the impact of various life stressors on individuals’ emotional well-being, specifically mental disorders, physical health conditions, social media usage, and employment status. This influences the ability of policies to combat the current rising mental health crisis and maximize people’s emotional well-being, making it crucial to gain a better understanding of these factors. The need for this research has been further exacerbated with the rise of the pandemic, as social media usage, changes in employment, and mental and physical health are more volatile than normal. This research study had 55 participants through the use of an anonymous survey sent to residents of Colorado ages 18 and older to analyze and visualize how emotional well-being is affected by these four life stressors. Conducting linear regressions, correlation tests, and plotting our results showed that employment status was the most statistically significant factor in an individual’s emotional well-being, followed by the prevalence of mental disorders. In turn, we recommend that policymakers and other stakeholders in Colorado actively work to combat the negative effects of volatile employment and mental disorders, which will ultimately better the emotional well-being of their citizens.