Demographics Analysis with Consumer Edge Credit & Debit Card Transaction Data

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. CE Transact Signal is an aggregated transaction feed that includes consumer transaction data on 100M+ credit and debit cards, including 14M+ active monthly users. Capturing online, offline, and 3rd-party consumer spending on public and private companies, data covers 12K+ merchants and deep demographic and geographic breakouts. Track detailed consumer behavior patterns, including retention, purchase frequency, and cross shop in addition to total spend, transactions, and dollars per transaction.

Consumer Edge’s consumer transaction datasets offer insights into industries across consumer and discretionary spend such as: • Apparel, Accessories, & Footwear • Automotive • Beauty • Commercial – Hardlines • Convenience / Drug / Diet • Department Stores • Discount / Club • Education • Electronics / Software • Financial Services • Full-Service Restaurants • Grocery • Ground Transportation • Health Products & Services • Home & Garden • Insurance • Leisure & Recreation • Limited-Service Restaurants • Luxury • Miscellaneous Services • Online Retail – Broadlines • Other Specialty Retail • Pet Products & Services • Sporting Goods, Hobby, Toy & Game • Telecom & Media • Travel

This data sample illustrates how Consumer Edge data can be used to compare demographics breakdown (age and income excluded in this free sample view) for one company vs. a competitor for a set period of time (Ex: How do demographics like wealth, ethnicity, children in the household, homeowner status, and political affiliation differ for Walmart vs. Target shopper?).

Inquire about a CE subscription to perform more complex, near real-time demographics analysis functions on public tickers and private brands like: • Analyze a demographic, like age or income, within a state for a company in 2023 • Compare all of a company’s demographics to all of that company’s competitors through most recent history

Consumer Edge offers a variety of datasets covering the US and Europe (UK, Austria, France, Germany, Italy, Spain), with subscription options serving a wide range of business needs.

Use Case: Demographics Analysis

Problem A global retailer wants to understand company performance by age group.

Solution Consumer Edge transaction data can be used to analyze shopper transactions by age group to understand: • Overall sales growth by age group over time • Percentage sales growth by age group over time • Sales by age group vs. competitors

Impact Marketing and Consumer Insights were able to: • Develop weekly reporting KPI's on key demographic drivers of growth for company-wide reporting • Reduce investment in underperforming age groups, both online and offline • Determine retention by age group to refine campaign strategy • Understand how different age groups are performing compared to key competitors

Corporate researchers and consumer insights teams use CE Vision for:

Corporate Strategy Use Cases • Ecommerce vs. brick & mortar trends • Real estate opportunities • Economic spending shifts

Marketing & Consumer Insights • Total addressable market view • Competitive threats & opportunities • Cross-shopping trends for new partnerships • Demo and geo growth drivers • Customer loyalty & retention

Investor Relations • Shareholder perspective on brand vs. competition • Real-time market intelligence • M&A opportunities

Most popular use cases for private equity and venture capital firms include: • Deal Sourcing • Live Diligences • Portfolio Monitoring

Public and private investors can leverage insights from CE’s synthetic data to assess investment opportunities, while consumer insights, marketing, and retailers can gain visibility into transaction data’s potential for competitive analysis, understanding shopper behavior, and capturing market intelligence.

Most popular use cases among public and private investors include: • Track Key KPIs to Company-Reported Figures • Understanding TAM for Focus Industries • Competitive Analysis • Evaluating Public, Private, and Soon-to-be-Public Companies • Ability to Explore Geographic & Regional Differences • Cross-Shop & Loyalty • Drill Down to SKU Level & Full Purchase Details • Customer lifetime value • Earnings predictions • Uncovering macroeconomic trends • Analyzing market share • Performance benchmarking • Understanding share of wallet • Seeing subscription trends

Fields Include: • Day • Merchant • Subindustry • Industry • Spend • Transactions • Spend per Transaction (derivable) • Cardholder State • Cardholder CBSA • Cardholder CSA • Age • Income • Wealth • Ethnicity • Political Affiliation • Children in Household • Adults in Household • Homeowner vs. Renter • Business Owner • Retention by First-Shopped Period ...

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

Core Database Statistics

Consumer Records: Over 269 million

Email Addresses: Over 160 million (verified and deliverable)

Phone Numbers: Over 76 million (mobile and landline)

Mailing Addresses: Over 116,000,000 (NCOA processed)

Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

Multi-Channel Campaign Applications

Deploy across all major marketing channels:

Email marketing and automation

Social media advertising

Search and display advertising (Google, YouTube)

Direct mail and print campaigns

Telemarketing and SMS campaigns

Programmatic advertising platforms

Data Quality & Sources

Our consumer data aggregates from multiple verified sources:

Public records and government databases

Opt-in subscription services and registrations

Purchase transaction data from retail partners

Survey participation and research studies

Online behavioral data (privacy compliant)

Technical Delivery Options

File Formats: CSV, Excel, JSON, XML formats available

Delivery Methods: Secure FTP, API integration, direct download

Processing: Real-time NCOA, email validation, phone verification

Custom Selections: 1,000+ selectable demographic and behavioral attributes

Minimum Orders: Flexible based on targeting complexity

Unique Value Propositions

Dual Spouse Targeting: Reach both household decision-makers for maximum impact

Cross-Platform Integration: Seamless deployment to major ad platforms

Real-Time Updates: Monthly data refreshes ensure maximum accuracy

Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

Compliance Management: Built-in opt-out and suppression list management

Ideal Customer Profiles

E-commerce retailers seeking customer acquisition

Financial services companies targeting specific demographics

Healthcare organizations with compliant marketing needs

Automotive dealers and service providers

Home improvement and real estate professionals

Insurance companies and agents

Subscription services and SaaS providers

Performance Optimization Features

Lookalike Modeling: Create audiences similar to your best customers

Predictive Scoring: Identify high-value prospects using AI algorithms

Campaign Attribution: Track performance across multiple touchpoints

A/B Testing Support: Split audiences for campaign optimization

Suppression Management: Automatic opt-out and DNC compliance

Pricing & Volume Options

Flexible pricing structures accommodate businesses of all sizes:

Pay-per-record for small campaigns

Volume discounts for large deployments

Subscription models for ongoing campaigns

Custom enterprise pricing for high-volume users

Data Compliance & Privacy

VIA.tools maintains industry-leading compliance standards:

CCPA (California Consumer Privacy Act) compliant

CAN-SPAM Act adherence for email marketing

TCPA compliance for phone and SMS campaigns

Regular privacy audits and data governance reviews

Transparent opt-out and data deletion processes

Getting Started

Our data specialists work with you to:

1. Define your target audience criteria

2. Recommend optimal data selections

3. Provide sample data for testing

4. Configure delivery methods and formats

5. Implement ongoing campaign optimization

Why We Lead the Industry

With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

Contact our team to discuss your specific ta...

Gain a competitive edge with our comprehensive Advertising Dataset, designed for marketers, analysts, and businesses to track ad performance, analyze competitor strategies, and optimize campaign effectiveness.

Dataset Features

Sponsored Posts & Ads: Access structured data on paid advertisements, including post content, engagement metrics, and platform details. Competitor Advertising Insights: Extract data on competitor campaigns, influencer partnerships, and promotional strategies. Audience Engagement Metrics: Analyze likes, shares, comments, and impressions to measure ad effectiveness. Multi-Platform Coverage: Track ads across LinkedIn, Instagram, Facebook, TikTok, Twitter (X), Pinterest, and more. Historical & Real-Time Data: Retrieve historical ad performance data or access continuously updated records for real-time insights.

Customizable Subsets for Specific Needs Our Advertising Dataset is fully customizable, allowing you to filter data based on platform, ad type, engagement levels, or specific brands. Whether you need broad coverage for market research or focused data for ad optimization, we tailor the dataset to your needs.

Popular Use Cases

Targeted Advertising & Audience Segmentation: Refine ad targeting by analyzing competitor content, audience demographics, and engagement trends. Campaign Performance Analysis: Measure ad effectiveness by tracking engagement metrics, reach, and conversion rates. Competitive Intelligence: Monitor competitor ad strategies, influencer collaborations, and promotional trends. Market Research & Trend Forecasting: Identify emerging advertising trends, high-performing content types, and consumer preferences. AI & Predictive Analytics: Use structured ad data to train AI models for automated ad optimization, sentiment analysis, and performance forecasting.

Whether you're optimizing ad campaigns, analyzing competitor strategies, or refining audience targeting, our Advertising Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

Comprehensive segments for gaming audience data. Dive into the data of gaming trends with our gaming databases. This dataset is best used for programmatic targeting of gaming audiences based on demographics, interests, and hardware use and more.

A global database of Direct Marketing Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future. Leverage up-to-date audience targeting population trends for market research, audience targeting, and sales territory mapping.

Self-hosted marketing population dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The Demographic Data is standardized, unified, and ready to use.

Use cases for the Global Consumer Behavior Database (Direct Marketing Data)

• Ad targeting

• B2B Market Intelligence

• Customer analytics

• Audience targeting

• Marketing campaign analysis

• Demand forecasting

• Sales territory mapping

• Retail site selection

• Reporting

• Audience targeting

Demographic data export methodology

Our population data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Historical population data (55 years)

• Changes in population density

• Urbanization Patterns

• Accurate at zip code and administrative level

• Optimized for easy integration

• Easy customization

• Global coverage

• Updated yearly

• Standardized and reliable

• Self-hosted delivery

• Fully aggregated (ready to use)

• Rich attributes

Why do companies choose our Consumer databases

• Standardized and unified demographic data structure

• Seamless integration in your system

• Dedicated location data expert

Note: Custom population data packages are available. Please submit a request via the above contact button for more details.

Data recorded during the data collection period 17 October– 11 December 2014.

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.

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.

Our proprietary People Data is a mobile user dataset that connects anonymous IDs to a wide range of attributes, including demographics, device ownership, audience segments, key locations, and more. This rich dataset allows our partner brands to gain a comprehensive view of consumers based on their personas, enabling them to derive actionable insights swiftly.

People Data Graph

• Record Count: 900 Million
• Capturing Frequency: Once per Event
• Delivering Frequency: Once per Month
• Updated: Monthly

People Data

Reach Our extensive data reach covers a variety of categories, encompassing user demographics, Mobile Advertising IDs (MAID), device details, locations, affluence, interests, traveled countries, and more. Data Export Methodology We dynamically collect and provide the most updated data and insights through the best-suited method at appropriate intervals, whether daily, weekly, monthly, or quarterly.

Business Needs

Our People Data caters to various business needs, offering valuable insights for consumer analysis, data enrichment, sales forecasting, and retail analytics, empowering brands to make informed decisions and optimize their strategies.

Dataset

This dataset was created by Emmanuel Ngunnzi

Released under MIT

Contents

As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.

              Facebook connects the world

              Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
              as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

This dataset provides IMDb user reviews for Christopher Nolan's highly anticipated film "**Oppenheimer**," which premiered on July 21, 2023. The film offers an engaging journey into history, recounting the extraordinary life of J. Robert Oppenheimer, a pivotal figure in the development of the atomic bomb during World War II. This collection of reviews allows for an insightful examination of public sentiment and audience reactions to this cinematic masterpiece.

Columns

• Title: The title given by the user to their review.
• Rating: The numerical score assigned by the user, expressed out of a maximum of 10.0.
• Review: The full textual content of the user's opinion or critique.

Distribution

The dataset is presented in a tabular format, comprising individual user reviews linked with their respective ratings. It contains 2445 entries or rows. The ratings span from 1.00 to 10.00, with a significant proportion of scores concentrated in the higher ranges. While specific file type details are not provided, data files of this nature are typically available in formats such as CSV.

Usage

This dataset is ideally suited for: * Analysing audience sentiment and public opinion regarding the film "Oppenheimer." * Performing Natural Language Processing (NLP) tasks on unstructured movie review text, such as topic modelling or entity extraction. * Developing and evaluating sentiment analysis models to predict review polarity. * Visualising movie ratings distribution and identifying trends in audience reception. * Academic and market research into film criticism, audience engagement, and the public's response to historical dramas.

Coverage

• Geographic Scope: Global, reflecting the worldwide reach of IMDb users.
• Time Range: The reviews are specifically for the film "Oppenheimer," released on July 21, 2023. The dataset itself was listed on 27 June 2025, suggesting it captures reactions around or after its release.
• Demographic Scope: Comprises user-submitted reviews from the IMDb platform; specific demographic breakdowns of reviewers are not included in the dataset details.

License

CC0

Who Can Use It

• Data Scientists and Analysts: To train machine learning models for text classification, sentiment analysis, and recommender systems.
• Film Critics and Researchers: To gain deeper insights into audience perceptions, identify recurring themes in feedback, and study the social impact of historical films.
• Academics: For studies on online review platforms, collective intelligence, and the dynamics of public opinion in entertainment.
• Marketing and Media Professionals: To understand audience reception, inform promotional strategies, and identify key discussion points surrounding the film.

Dataset Name Suggestions

• Oppenheimer IMDb Reviews Dataset
• Oppenheimer Film Audience Sentiment Data
• Christopher Nolan's Oppenheimer User Reviews
• Movie Ratings: Oppenheimer Audience Feedback

Attributes

Original Data Source: Oppenheimer IMDb reviews

Here are a few use cases for this project:

1. Demographic Analysis in Retail: The "age&gender" computer vision model could be used in stores or shopping malls to analyze customer demographics. It will help in identifying the age and gender groups of shoppers, enabling store managers to customize marketing strategies, store layouts, or product placement according to different groups' preferences.

2. Audience Measurement in Media and Advertising: TV channels, billboard owners, or digital marketers could use this model to determine who their primary audience is, by identifying the age group and gender of viewers or passers-by. This data will allow them to tailor their content and advertising to attract and retain their target audience effectively.

3. Social Research and Urban Planning: Researchers could deploy this model in public areas to gather demographic data which could inform a range of policies from social services provision to creating more inclusive urban spaces. It can also be used to gain insights into population movements and density in cities.

4. Interactive Installations: In museums, expos, and other public installations, the age&gender model could be used to tailor the information or experience to the visitor automatically, based on their detected age group and gender, resulting in a more personalized encounter.

5. Healthcare and Well-being: For applications where users are comfortable sharing this data, gym clubs or wellness centers could use this model to provide personalized training routines or wellness plans according to the detected age and gender groups. This could help to improve the effectiveness of the user's workouts or wellness regimes.

This dataset provides detailed, event-level social media engagement metrics, tracking user interactions across multiple platforms and content types. It enables brands to analyze engagement trends, measure campaign effectiveness, and optimize content strategies for maximum reach and impact. With granular data on user actions, post metadata, and audience demographics, it supports advanced analytics and actionable insights for marketing teams.

QuoteWay Canada provides extensive Demographic Data, ideal for businesses seeking detailed audience targeting. Our Demographic Data encompasses approximately 1.3M records, specifically collected for life insurance purposes and currently resting for about 3 months without contact. This Demographic Data includes age, gender, address, and identity data, ensuring a comprehensive view of the Canadian audience.

Use Cases of Demographic Data: - Targeted Marketing Campaigns: Utilize our Demographic Data to launch highly targeted marketing campaigns with precise audience segmentation. - Customer Profiling: Create detailed customer profiles using our rich Demographic Data. - Market Research: Conduct thorough market research with reliable Demographic Data for accurate consumer insights. - Product Development: Use Demographic Data to inform product development based on the characteristics and identity of your target audience. - Geographic Analysis: Perform geographic analysis with 96% valid postal codes from our Demographic Data. - Email Campaigns: Boost email marketing success rates with 98% valid emails from our Demographic Data. - Telemarketing: Improve telemarketing outcomes using 70% valid phone numbers in our Demographic Data.

Key Benefits of Demographic Data: - High Accuracy: Our Demographic Data is verified with 96% valid postal codes, 98% valid emails, and 70% valid phone numbers. - Comprehensive Dataset: Access a large dataset of approximately 1.3M records, including detailed demographic information and identity data. - Fresh Data: The Demographic Data has been resting for about 3 months, ensuring it is not overused. - Versatile Use: Suitable for various applications such as marketing, research, advertising and product development. - Compliance Ready: Our Demographic Data is ready to use under QuoteWay Canada Inc., ensuring compliance and ease of use. - Life Insurance Focused: The data was initially collected for life insurance purposes, providing a unique consumer segment. - Reliable Source: QuoteWay's commitment to quality ensures that our Demographic Data is reliable and effective, using our Advertising Data.

By leveraging QuoteWay Canada's Demographic and Identity Data, businesses can achieve greater accuracy and success in their consumer outreach efforts. The comprehensive and verified nature of our Demographic Data makes it an invaluable resource for any organization looking to enhance its audience targeting strategies.

OverviewThe BuzzFeed dataset, officially known as the BuzzFeed-Webis Fake News Corpus 2016, comprises content from 9 news publishers over a 7-day period close to the 2016 US election. It was created to analyze the spread of misinformation and hyperpartisan content on social media platforms, particularly Facebook.Dataset CompositionNews Articles: The dataset includes 1,627 articles from various sources:826 from mainstream publishers256 from left-wing publishers545 from right-wing publishersFacebook Posts: Each article is associated with Facebook post data, including metrics like share counts, reaction counts, and comment counts.Comments: The dataset includes nearly 1.7 million Facebook comments discussing the news content.Fact-Check Ratings: Each article was fact-checked by professional journalists at BuzzFeed, providing veracity assessments.Key FeaturesPublisher Information: The dataset covers 9 publishers, including 6 hyperpartisan (3 left-wing and 3 right-wing) and 3 mainstream outlets.Temporal Aspect: The data was collected over seven weekdays (September 19-23 and September 26-27, 2016).Verification Status: All publishers included in the dataset had earned Facebook's blue checkmark, indicating authenticity and elevated status.Metadata: Includes various metrics such as publication dates, post types, and engagement statistics.Potential ApplicationsThe BuzzFeed dataset is valuable for various research and analytical purposes:News Veracity Assessment: Researchers can use machine learning techniques to classify articles based on their factual accuracy.Social Media Analysis: The dataset allows for studying how news spreads on platforms like Facebook, including engagement patterns.Hyperpartisan Content Study: It enables analysis of differences between mainstream and hyperpartisan news sources.Content Strategy Optimization: Media companies can use insights from the dataset to refine their content strategies.Audience Analysis: The data can be used for demographic analysis and audience segmentation.This dataset provides a comprehensive snapshot of news dissemination and engagement on social media during a crucial period, making it a valuable resource for researchers, data scientists, and media analysts studying online information ecosystems.

Overview:The VIP Actress and Models Service dataset is a comprehensive collection of fictional data meticulously curated for the purpose of managing and optimizing a high-end service catering to the needs of clients seeking exclusive experiences with renowned actresses and models. This dataset serves as a valuable resource for service providers in this niche industry, offering insights into customer preferences, service utilization, and satisfaction levels.Dataset Fields:Customer_ID: A unique identifier for each customer.Customer_Name: The name of the customer.Customer_Age: The age of the customer.Customer_Gender: The gender of the customer (e.g., Male, Female, Non-binary).Customer_Location: The location of the customer (e.g., City, State, Country).Customer_Email: The email address of the customer.Customer_Phone: The phone number of the customer.Service_Type: The type of service requested by the customer (e.g., Actress, Model).Service_Date: The date on which the service was requested.Service_Duration: The duration of the service in hours.Service_Rate: The rate charged for the service.Service_Requested_Actress_Model: The name of the requested actress or model.Service_Description: Additional details or notes about the service request.Payment_Status: The payment status (e.g., Paid, Pending, Refunded).Customer_Review: A customer review or feedback on the service.Customer_Rating: The rating provided by the customer (e.g., on a scale of 1 to 5).Use Cases:Service Optimization: Service providers can use this dataset to analyze customer preferences and tailor offerings accordingly, ensuring a personalized experience.Financial Analysis: By examining payment statuses and rates, businesses can track revenue and financial performance.Customer Satisfaction: Customer reviews and ratings enable evaluation of service quality and areas for improvement.Market Insights: Geographical and demographic data can inform expansion strategies and target audience selection.Important Notes:This dataset is entirely fictitious and intended for demonstration and analytical purposes only.Any resemblance to real individuals or entities is purely coincidental.Ensure compliance with all relevant privacy and data protection regulations when using this dataset.The VIP Actress and Models Service dataset is a valuable asset for businesses looking to excel in the luxury entertainment industry by providing top-tier services tailored to the unique desires of their clientele.http://callgirlsmanali.comhttp://trishadehradun.inhttp://callgirlsandheri.inhttp://callgirlsinharidwar.comhttp://callgirlsinharidwar.inhttp://callgirlsinpunee.inhttp://muskangirlsdwarka.inhttps://escortsindwarkaa.inhttps://rishikeshgirls.inhttp://shipranoida.inhttps://singledate.inhttp://girlsingurgaon.inhttp://girlsinindirapuram.comhttp://mumbaimodels.orghttp://callgirlgurgaon.inhttp://callgirlrishikesh.inhttp://callgirlharidwar.inhttp://callgirlujjain.inhttps://callgirlsaket.inhttp://akankshagurgaon.inhttp://callgirlmussooriee.inhttps://callgirlharidwarr.inhttp://callgirlagra.inhttps://callgirlsudaipur.inhttps://callgirlsodala.inhttp://saltlake.callgirlsinpunee.inhttps://callgirldelhii.in

This dataset contains details for 10,000 top-rated movies from TMDB, updated as of 26th July 2022. Its primary purpose is to facilitate text preprocessing and cleansing for Natural Language Processing (NLP) tasks related to movie data. It is also highly suitable for developing content-based and collaborative filtering recommendation engines. This resource offers a rich context for understanding movie popularity, genres, and audience reception.

Columns

• id: The unique identification number for the movie on the website.
• title: The name of the movie.
• genre: The categorisation of the movie, such as crime, adventure, or drama.
• original_language: The initial language in which the movie was released.
• overview: A brief summary or synopsis of the movie.
• popularity: A metric indicating the movie's popularity.
• release_date: The date when the movie was first released.
• vote_average: The average rating given to the movie by voters.
• vote_count: The total number of votes received by the movie.

Distribution

This dataset comprises approximately 10,000 records, typically provided in a CSV file format. Specific row counts for a sample file are updated separately. The dataset includes unique values for movie IDs, with original_language predominantly being English (around 78%) and French (7%). Movie genres include Comedy (7%) and Drama (6%), with a wide array of other genres. Release dates span a broad period from 1902 to 2022, with the majority of entries from 1998 onwards. Popularity scores range from 0.6 to over 10,000, and vote averages are generally between 4.6 and 8.7, with vote counts reaching up to 31,900.

Usage

This dataset is ideal for: * Performing extensive text preprocessing and cleansing for NLP applications on movie descriptions and titles. * Building various movie recommendation systems, including content-based recommenders and collaborative filtering engines. * Analysing trends in movie popularity, audience ratings, and language distribution. * Developing data science projects focused on entertainment and media consumption.

Coverage

The dataset's geographic scope is global. It covers movies released between 17th April 1902 and 13th July 2022, with the dataset itself assembled with data up to 26th July 2022. There are no specific demographic notes available, but it broadly covers top-rated films from the TMDB database.

License

CCO

Who Can Use It

This dataset is suitable for: * Data Scientists and Machine Learning Engineers working on recommendation systems or NLP projects. * Researchers studying film industry trends, audience engagement, or language processing. * Developers looking to integrate movie data into applications. * Anyone interested in exploratory data analysis within the entertainment sector.

Dataset Name Suggestions

• TMDB Top Movies Dataset
• Movie Data for NLP & Recommendations
• Global Movie Popularity Dataset
• Film Data Hub

Attributes

Original Data Source: TMDB Movies Dataset

The Global Audience Segments dataset categorizes people in Germany based on their travel to relevant stores, businesses, or other points of interest - therefore exposing audience media habits, hobbies, and consumer behaviors.

This dataset is a valuable tool for marketers and researchers aiming to understand and reach diverse German and global audiences with various interests and demographic profiles.

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.