How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

In 2023, Meta Platforms had a total annual revenue of over 134 billion U.S. dollars, up from 116 billion in 2022. LinkedIn reported its highest annual revenue to date, generating over 15 billion USD, whilst Snapchat reported an annual revenue of 4.6 billion USD.

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.

NoSQL Database Market was valued at $9.38 Billion in 2023, and is projected to reach $USD 86.48 Billion by 2032, at a CAGR of 28% from 2023 to 2032.

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.

Multilingual Mobile App Reviews Dataset 2025

Overview

This comprehensive synthetic dataset contains 2,514 authentic mobile app reviews spanning 40+ popular applications across 24 different languages, making it ideal for multilingual NLP, sentiment analysis, and cross-cultural user behavior research.

Dataset Statistics

• Total Records: 2,514 reviews
• Columns: 15 features
• Languages Covered: 24 international languages
• Apps Included: 40+ popular mobile applications
• Time Range: 2023-2025 (2-year span)
• File Format: CSV
• Data Quality: Intentionally includes missing values and mixed data types for data cleaning practice

Column Specifications

Note: Data types marked with asterisk require cleaning/conversion

Language Distribution

The dataset includes reviews in 24 languages: - European: English (en), Spanish (es), French (fr), German (de), Italian (it), Russian (ru), Polish (pl), Dutch (nl), Swedish (sv), Danish (da), Norwegian (no), Finnish (fi) - Asian: Chinese (zh), Hindi (hi), Japanese (ja), Korean (ko), Thai (th), Vietnamese (vi), Indonesian (id), Malay (ms) - Other: Arabic (ar), Turkish (tr), Filipino (tl)

Application Categories

Reviews cover 18 distinct categories: - Social Networking - Entertainment
- Productivity - Travel & Local - Music & Audio - Video Players & Editors - Shopping - Navigation - Finance - Communication - Education - Photography - Dating - Business - Utilities - Health & Fitness - Games - News & Magazines

Popular Apps Included

40+ applications including: - Social: WhatsApp, Instagram, Facebook, Snapchat, TikTok, LinkedIn, Twitter, Reddit, Pinterest - Entertainment: YouTube, Netflix, Spotify - Productivity: Microsoft Office, Google Drive, Dropbox, OneDrive, Zoom, Discord - Travel: Uber, Lyft, Airbnb, Booking.com, Google Maps, Waze - Finance: PayPal, Venmo - Education: Duolingo, Khan Academy, Coursera, Udemy - Tools: Grammarly, Canva, Adobe Photoshop, VLC, MX Player

Geographic Distribution

Reviews from 24 countries across all continents: - Asia: China, India, Japan, South Korea, Thailand, Vietnam, Indonesia, Malaysia, Philippines, Pakistan, Bangladesh - Europe: Germany, United Kingdom, France, Italy, Spain, Russia, Turkey, Poland - Americas: United States, Canada, Brazil, Mexico - Oceania: Australia - Africa: Nigeria

Data Quality Features

Intentional data challenges for learning: - Missing Values: Strategic nulls in review_text (63), rating (38), user_country (50), user_gender (88), app_version (25) - Data Type Issues: - user_id stored as strings (should be integers) - user_age as floats (should be integers)
- Some ratings as strings (should be floats) - Some helpful_votes as strings (should be integers) - Mixed Version Formats: "1.4", "v8.9", "2.8.37.5926", "14.1.60.318-beta"

Use Cases

This dataset is perfect for: - Multilingual NLP projects and sentiment analysis - Cross-cultural user behavior analysis - App store analytics and rating prediction - Data cleaning and preprocessing practice - Text classification across multiple languages - Time series analysis of app reviews - Geographic sentiment analysis - Data engineering pipeline development

Data Cleaning Opportunities

• Convert string IDs to integers
• Standardize rating values to float
• Han...

During a 2024 survey, 77 percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just 23 percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis.

              Social media: trust and consumption

              Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than 35 percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than 50 percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media.

              What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis.
              Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers.
              Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Context

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fb984828c354c4d8e72965aa78d5503ee%2Fpinterest2.png?generation=1700270897504206&alt=media" alt="">

Based on their wikipedia page

Pinterest is an American image-sharing and social media service designed to enable saving and discovery of information (specifically "ideas") like recipes, home, style, motivation, and inspiration on the internet using images and, on a smaller scale, animated GIFs and videos, in the form of pinboards. The site was created by Ben Silbermann, Paul Sciarra, and Evan Sharp and it is operated by now Pinterest, Inc., and headquartered in San Francisco.

These reviews were extracted from its Google Store page.

Usage

This dataset should paint a good picture on what is the public's perception of the app over the years. Using this dataset, we can do the following

1. Extract sentiments and trends
2. Identify which version of the app had the most positive feedback, the worst.
3. Use topic modeling to identify the pain points of the application.

(AND MANY MORE!)

Note

Images generated using Bing Image Generator

Market Size and Growth: The global NoSQL database market is estimated to reach USD XXX million by 2033, growing at a CAGR of XX% from 2025 to 2033. Key factors driving this growth include the increasing volume of unstructured data, the need for scalable and flexible data management solutions, and the rise of big data analytics. Key Trends and Segments: The market is segmented based on application (e-commerce, social networking, data analytics, etc.) and type (column, document, key-value, graph). Key trends include the adoption of multi-model databases, the emergence of cloud-based NoSQL solutions, and the growing importance of data security and compliance. Notable players in the market include DynamoDB, ObjectLabs Corporation, Skyll, MarkLogic, InfiniteGraph, Oracle, MapR Technologies, the Apache Software Foundation, Basho Technologies, and Aerospike. The North America region is projected to dominate the market, followed by Asia Pacific and Europe.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

Free-Cash-Flow-To-The-Firm Time Series for Bumble Inc. Bumble Inc. provides online dating and social networking applications in North America, Europe, internationally. It owns and operates websites and applications that offers subscription and in-app purchases of products. The company operates apps, including Bumble, a dating app built with women at the center, where women make the first move; Badoo, the web and mobile free-to-use dating app; Bumble BFF and Bumble Bizz Modes that have a format similar to the date mode requiring users to set up profiles and matching users through yes and no votes, similar to the dating platform; and Bumble for Friends, a friendship app where people in all stages of life can meet people nearby and create meaningful platonic connections, as well as Geneva app where users can create and join chat, forum, audio, video, and broadcast rooms. The company was founded in 2020 in and is headquartered in Austin, Texas.

AI Content Detector Market size is growing at a moderate pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024 to 2031.

Global AI Content Detector Market Drivers

Rising Concerns Over Misinformation: The proliferation of fake news, misinformation, and inappropriate content on digital platforms has led to increased demand for AI content detectors. These systems can identify and flag misleading or harmful content, helping to combat the spread of misinformation online.

Regulatory Compliance Requirements: Stringent regulations and legal obligations regarding content moderation, data privacy, and online safety drive the adoption of AI content detectors. Organizations need to comply with regulations such as the General Data Protection Regulation (GDPR) and the Digital Millennium Copyright Act (DMCA), spurring investment in AI-powered content moderation solutions.

Growing Volume of User-Generated Content: The exponential growth of user-generated content on social media platforms, forums, and websites has overwhelmed traditional moderation methods. AI content detectors offer scalable and efficient solutions for analyzing vast amounts of content in real-time, enabling platforms to maintain a safe and healthy online environment for users.

Advancements in AI and Machine Learning Technologies: Continuous advancements in artificial intelligence and machine learning algorithms have enhanced the capabilities of content detection systems. AI models trained on large datasets can accurately identify various types of content, including text, images, videos, and audio, with high precision and speed.

Brand Protection and Reputation Management: Businesses prioritize brand protection and reputation management in the digital age, as negative content or misinformation can severely impact brand image and consumer trust. AI content detectors help organizations identify and address potentially damaging content proactively, safeguarding their reputation and brand integrity.

Demand for Personalized User Experiences: Consumers increasingly expect personalized online experiences tailored to their preferences and interests. AI content detectors analyze user behavior and content interactions to deliver relevant and engaging content, driving user engagement and satisfaction.

Adoption of AI-Powered Moderation Tools by Social Media Platforms: Major social media platforms and online communities are investing in AI-powered moderation tools to enforce community guidelines, prevent abuse and harassment, and maintain a positive user experience. The need to address content moderation challenges at scale drives the adoption of AI content detectors.

Mitigation of Online Risks and Threats: Online platforms face various risks and threats, including cyberbullying, hate speech, terrorist propaganda, and child exploitation content. AI content detectors help mitigate these risks by identifying and removing harmful content, thereby creating a safer online environment for users.

Cost and Resource Efficiency: Traditional content moderation methods, such as manual review by human moderators, are time-consuming, labor-intensive, and costly. AI content detectors automate the moderation process, reducing the need for human intervention and minimizing operational expenses for organizations.

Here are a few use cases for this project:

1. Supermarket Inventory Management: Use the model to automatically track inventory levels of various Nescafe coffee products on store shelves. The system can notify store employees when stock needs replenishment or reorganization, improving store efficiency and customer satisfaction.

2. Price Comparison App Integration: Integrate the "05082022_coffee_Norm" model into a smartphone price comparison app. Users can take a picture of the Nescafe products at the store, and the app will recognize the specific product and provide them with the best prices available at nearby stores or online retailers.

3. Smart Vending Machines: Upgrade vending machines with the computer vision model to offer a wider range of Nescafe coffee products. The system can detect the specific product a customer selects, automatically charge them for it, and dispense it, enhancing the user experience.

4. Distribution and Warehouse Automation: Apply the model in distribution centers and warehouses to improve sorting, packaging, and shipment of Nescafe coffee products. The system can recognize the different product types and ensure that they are correctly handled and shipped to the appropriate destinations, reducing errors and inefficiencies.

5. Consumer Insights and Market Research: Use the model to analyze social media images, marketing campaigns, and other sources to gain insights into customer preferences, brand association, and product usage patterns. This valuable data can help Nescafe make more informed decisions when developing new products or marketing strategies.

The Canadian contribution and data set prepared as part of the Global Media and Internet Concentration (GMIC) project offers an independent academic, empirical and data-driven analysis of a deceptively simple yet profoundly important question: have telecom, media and internet markets become more concentrated over time, or less? Media Ownership and Concentration is presented from more than a dozen sectors of the telecom-media-internet industries, including film, music and book industries. Note: The Master GMICP Workbook was revised to remove instances where App Store and advertising revenue for Advertising-based Video-on-Demand (AVOD) services delivered over the Internet had been double counted in the original data set released through Dataverse. The text of the report was also revised to reflect these corrections.

How much time do people spend on social media? As of 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

Database Engines Market Outlook

The global database engines market size was valued at USD 40 billion in 2023 and is projected to reach USD 68 billion by 2032, growing at a CAGR of 6.2% during the forecast period. This growth is driven by the increasing demand for efficient data management solutions, the rapid proliferation of data, and advancements in cloud computing technologies.

The growth of the database engines market is primarily fueled by the exponential increase in data generated across various industry verticals. Organizations are seeking robust and scalable solutions to manage, store, and analyze massive volumes of data. The surge in digital transformation initiatives and the growing adoption of big data analytics are accelerating the demand for advanced database engines. Additionally, the rise in cloud-based services has paved the way for more flexible and cost-effective solutions, further bolstering market growth.

Another significant growth factor is the increasing adoption of Internet of Things (IoT) technologies. The IoT ecosystem generates vast amounts of real-time data that require sophisticated database engines for processing and analysis. This surge in data from IoT devices necessitates the deployment of efficient database management systems. Furthermore, the growing emphasis on artificial intelligence (AI) and machine learning (ML) technologies, which rely heavily on data, is also propelling the adoption of database engines.

The regulatory landscape is also playing a crucial role in shaping the database engines market. Compliance with data protection and privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), is driving the need for secure and reliable database solutions. Organizations are prioritizing data security and integrity, thereby increasing investments in advanced database engines that offer robust security features and regulatory compliance capabilities.

The rise of Open-Source Database Software is becoming a transformative force in the database engines market. These solutions offer organizations the flexibility to customize and optimize their database environments without the constraints of proprietary software. Open-source databases, such as PostgreSQL and MySQL, have gained popularity due to their cost-effectiveness and community-driven development models. They provide robust performance and scalability, making them suitable for a wide range of applications, from small startups to large enterprises. As more organizations seek to reduce costs and increase control over their data infrastructure, the adoption of open-source database software is expected to grow, further driving innovation and competition in the market.

Regionally, North America holds a dominant position in the database engines market, owing to the presence of major technology players and the early adoption of advanced technologies. The Asia Pacific region is expected to witness significant growth during the forecast period, driven by the rapid digitalization initiatives, increasing investments in IT infrastructure, and the growing number of small and medium enterprises (SMEs) adopting database solutions. Europe is also a notable market, with a strong emphasis on data protection and privacy regulations driving the demand for secure database engines.

Type Analysis

The database engines market is categorized into several types, including Relational, NoSQL, NewSQL, In-Memory, and Others. Relational database engines, based on the traditional table structure, remain the most widely used type due to their reliability, robustness, and ability to handle complex queries. These engines are integral to various enterprise applications, offering a structured way to manage data through predefined schemas. The maturity and extensive support of relational databases make them a preferred choice for many organizations, especially in industries like finance and healthcare where data integrity is paramount.

NoSQL database engines have gained significant traction in recent years, primarily due to their flexibility and scalability. Unlike traditional relational databases, NoSQL databases do not rely on a fixed schema, making them suitable for handling unstructured and semi-structured data. This characteristic is particularly advantageous for applications involving big data and real-time web applications. The rise of e-commerce, social media, and IoT app

Here are a few use cases for this project:

1. Food Inventory Tracking: Use the "Chicken wing" model in restaurants and grocery stores to automate inventory tracking of chicken wings in storage or on display. The model can count the number of wings and update inventory records more efficiently, reducing manual labor and errors.

2. Portion Control Assistance: Employ the model in meal planning apps to help users maintain a balanced diet. The model can analyze images of chicken wings and automatically estimate their quantity and size, providing users with nutritional information and aiding portion control.

3. Quality Control in Poultry Industry: Utilize the "Chicken wing" model to inspect the quality of chicken wings in the poultry industry, enabling prompt identification of visual anomalies, such as improperly cut or damaged pieces, and facilitating a more efficient sorting process.

4. Assistance in Cooking Apps and Websites: Integrate the model into cooking apps and websites to identify chicken wing recipes and suggest related recipes based on the input image. Users can quickly find recipes or cooking instructions tailored to the specific type of chicken wing they have on hand.

5. Social Media Food Recognition: Deploy the "Chicken wing" model in social media platforms and food photograph-sharing applications to recognize and categorize chicken wing dishes. This will enable users to more efficiently search for and discover new chicken wing preparation styles and recipes based on visual content.

Here are a few use cases for this project:

1. Online Retail Store: The "Assembled" model could be used by an online fashion retailer to automatically categorize and sort incoming inventory by clothing type. This would significantly streamline the product listing process and ensure accurate search results for customers.

2. Fashion Trend Tracking: Firms involved in fashion market research might use the "Assembled" model to analyze and identify trends in street fashion, by scanning and interpreting public footage or photos shared on social media.

3. Personal Wardrobe Assistant: An application could use the "Assembled" model for managing users' wardrobes, suggesting outfits based on specific clothing items identified or sorting clothes by type for easier organization.

4. Dress Code Enforcement: In environments where specific attire is required or certain clothing is not allowed (such as schools or professional workplaces), the "Assembled" model could be employed to enforce these rules and identify transgressions.

5. Aid for Visually Impaired: Apps or wearable smart devices could employ the "Assembled" model to help visually impaired individuals identify their clothing, potentially offering them greater independence in their attire choices.