During a survey fielded in the United States in April and May 2022, **** of responding internet users aged between 18 and 34 years said they went to the movies often or sometimes. Among respondents from the 35-44 age group, the share stood at ** percent. ***** out of 10 interviewees age ** and over said they never went to see a film in theaters. More than **** of Hispanic adults in the U.S. reported going to the movies often or sometimes in 2022.

In 2021, approximately ** percent of moviegoers in the United States and Canada identified as Caucasian and/or White. Viewers who identified as Hispanic and/or Latino accounted for ** percent of the total.

A survey fielded in the United States in 2025 revealed that ** percent of baby boomers never or rarely went to the cinema. On the contrary, younger consumers were more likely to go often - about a third of Gen Z movie-goers went to the movies a few times a month.

In 2019, there were *** million frequent moviegoers aged 60 or above, up from *** million in the previous year. Conversely, more 12 to 17-year-olds were visiting the cinema regularly that year. Why do some people go to movie theaters less than they used to? There is a clear overall change in movie-going frequency among U.S. adults – ** percent of respondents to a 2018 survey said that they saw fewer movies in theaters than five years ago. Whilst many consumers still prefer to see movies in theaters upon their release, the hobby is arguably less popular than it used to be. Trips to the cinema can be costly – on average, a ticket to a North American movie theater cost **** U.S. dollars in 2018. For many Americans, this is too expensive, especially with streaming services like Netflix, Hulu, and Amazon offering subscribers better value for money. It is no coincidence that the appeal of the movie theater has waned as streaming services have grown in popularity. It is now the norm to subscribe to a combined TV and movie streaming service, and whilst the **** dollar fee for a movie theater ticket covers just one showing, several streaming platforms allow consumers to enjoy content whenever and wherever they want for similar price per month. Equally, a movie must appeal to film fans before they go to see it (particularly if they consider the price higher than they would like) and if for several months nothing comes up that interests them, it is only natural that they will visit theaters less regularly. Again, the appeal of a movie often largely depends on age. Far more younger adults are likely to watch live-action Disney remakes like ‘The Lion King’ than their older peers, for instance – and younger viewers also watch dystopian content more than older generations.

MovieLens 1M Dataset

Overview

The MovieLens 1M dataset is a collection of movie ratings provided by the GroupLens Research Project at the University of Minnesota. This dataset contains 1,000,209 anonymous ratings of approximately 3,900 movies made by 6,040 users who joined MovieLens in 2000. It is widely used in research on recommendation systems, data mining, and machine learning.

Contents

• Ratings: 1,000,209 ratings on a scale of 1-5 stars.
• Movies: Information on 3,883 movies including titles, genres, and release dates.
• Users: Demographic information for 6,040 users including age, gender, occupation, and zip codes.

Features

• Ratings: Each rating has the following attributes:

  • UserID: A unique identifier for the user.
  • MovieID: A unique identifier for the movie.
  • Rating: The rating given by the user (1-5 stars).
  • Timestamp: The time the rating was made.

• Movies: Each movie entry includes:

  • MovieID: A unique identifier for the movie.
  • Title: The title of the movie.
  • Genres: The genres associated with the movie (e.g., Action, Comedy).

• Users: Each user entry includes:

  • UserID: A unique identifier for the user.
  • Gender: The gender of the user.
  • Age: The age of the user.
  • Occupation: The occupation of the user.
  • Zip-code: The zip-code of the user.

Use Cases

• Recommendation Systems: Ideal for building and testing collaborative filtering and content-based recommendation algorithms.
• Data Mining: Suitable for discovering patterns and insights in user behavior.
• Machine Learning: Can be used for training predictive models for various tasks such as predicting user ratings, movie popularity, etc.

Format

The dataset is provided in plain text format with tab-separated values, making it easy to load and process using various data analysis tools and programming languages.

Acknowledgements

This dataset is made available by the GroupLens Research Project at the University of Minnesota. For more information about their work, visit the GroupLens website.

This dataset provides national theater box office statistics for films distributed by the Administrative Institution National Film and Audiovisual Culture Center. The data is up to the last Sunday before the announcement date and does not include films that have not been screened for less than 7 calendar days. The earliest CSV format data in this dataset begins on July 30, 2018, and the earliest JSON format data begins on March 1, 2020. JSON format queries require entering the start and end dates (in the format of year, month, and day), and can provide data for a maximum of 90 days at a time.

As of May 2022, around ** percent of Hispanic internet users surveyed in the United States said they went to the movies sometimes. Approximately ** percent of Black, non-Hispanic respondents stated that they often went to see a film in theaters.

U.S. Movie Theatres Market size was valued at USD 419.6 Billion in 2024 and is projected to reach USD 695.37 Billion by 2031, growing at a CAGR of 7.19% during the forecast period 2024-2031.U.S. Movie Theatres Market DriversThe growth of the U.S. movie theater market is significantly bolstered by the rise of premium viewing experiences and the inclusion of alternative content. Premium viewing experiences, such as IMAX, 3D, and 4D screenings, provide audiences with unparalleled visual and auditory stimulation that cannot be replicated at home. These formats offer superior picture quality, enhanced sound systems, and additional sensory effects like moving seats and environmental changes (e.g., wind, and scents). The allure of these immersive experiences encourages moviegoers to pay a premium price, thereby increasing revenue for theater operators. Additionally, luxury cinemas with plush reclining seats, high-quality food and beverage options, and personalized services create a more comfortable and enjoyable environment, appealing to a demographic willing to spend more for a higher level of comfort and exclusivity. This segment of the market not only attracts regular movie enthusiasts but also those seeking a special outing or a unique entertainment experience.The inclusion of alternative content is transforming the traditional role of movie theaters. Beyond standard film screenings, theaters are diversifying their offerings to include live broadcasts of concerts, sports events, and theatrical productions. This expansion taps into different audience segments and broadens the appeal of theaters. For example, fans of a particular band might flock to a live concert broadcast, or sports enthusiasts might gather to watch a major game on the big screen. These events can turn theaters into multi-purpose venues that cater to a variety of interests and entertainment needs. The diversification into alternative content not only provides additional revenue streams but also helps fill seats during non-peak movie hours, thereby optimizing the use of theater space.

Movie Theater Market Outlook

The global movie theater market size was valued at USD 42.1 billion in 2023 and is projected to reach USD 63.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 4.6% during the forecast period. The growth of this market is driven by the increasing demand for immersive cinematic experiences and advancements in theater technologies. The rising popularity of blockbuster movies and the expansion of multiplex chains in emerging markets are also contributing significantly to this growth.

The growth of the movie theater market is notably influenced by consumer preference for high-quality audiovisual entertainment. With the rise of streaming services, theaters have had to innovate by enhancing the viewer experience through advancements in screen technology, including IMAX, 3D, and 4D formats. The draw of these premium formats lies in their ability to provide an immersive experience that is difficult to replicate at home. Furthermore, the advent of high-definition projection systems and state-of-the-art sound systems is spearheading the transformation of traditional movie theaters into advanced entertainment hubs.

Another crucial growth factor is the modernization and refurbishment of existing theaters. Many older theaters are undergoing significant upgrades to offer more comfortable and luxurious seating, better concession options, and enhanced sound and visual systems. These improvements are aimed at attracting more customers, particularly in urban areas where competition from home entertainment options is fiercest. Additionally, the expansion of multiplexes in emerging economies is driving market revenue as these regions witness increased disposable incomes and urbanization trends that favor out-of-home entertainment.

The strategic partnerships and collaborations between movie production houses and theater chains also play a pivotal role in market growth. Exclusive releases and advanced booking options have transformed the movie-going experience, making it more convenient and appealing. Coupled with aggressive marketing strategies and the creation of loyalty programs, these initiatives help theaters maintain a steady influx of patrons. Moreover, specialty screenings and events, such as film festivals and live-streamed concerts, have diversified the traditional business model, adding new revenue streams for theater operators.

Cinema Seating has become a pivotal aspect of the movie theater experience, as theaters strive to enhance comfort and luxury for their patrons. The evolution of seating options, from traditional rows to plush recliners with adjustable features, reflects the industry's commitment to providing a superior viewing environment. Modern theaters are increasingly incorporating features such as heated seats, extra legroom, and even private pods to cater to diverse audience preferences. This focus on seating innovation not only elevates the overall cinematic experience but also serves as a competitive differentiator in attracting more visitors. As consumer expectations continue to rise, the role of Cinema Seating in shaping the future of movie theaters cannot be understated.

Geographically, the Asia Pacific region is emerging as a significant market for movie theaters due to rapid urbanization and a burgeoning middle class with increased spending power. China and India, in particular, are witnessing a surge in the construction of new theaters and multiplex chains. North America remains a mature market but continues to generate substantial revenue, driven by technological advancements and the consistent release of high-grossing films. Europe and Latin America also present growth opportunities, though these markets are relatively more fragmented. The Middle East & Africa, while smaller in market size, are experiencing growth due to investments in entertainment infrastructure and a growing youth population.

Screen Type Analysis

The screen type segment is a critical component of the movie theater market, encompassing IMAX, 3D, 2D, and 4D formats. IMAX screens, known for their large size and superior image quality, offer an unparalleled viewing experience that draws moviegoers willing to pay a premium for blockbuster films and special screenings. The IMAX format has seen substantial growth due to its ability to provide an immersive experience that is difficult to replicate, even with advanced home theater systems. This format is particularly popular for action-packed and visually stunning f

This dataset simulates ratings given by users of different ages and genders to various movie genres. It includes user IDs, age, gender, preferred genre, rating, and viewing frequency. The data supports analysis of audience behavior, genre preference trends, or the development of recommender systems.

Number of Businesses statistics on the Movie Theaters industry in the US

Description: This dataset provides comprehensive movie statistics compiled from multiple sources, including Wikipedia, The Numbers, and IMDb. It offers a rich collection of information and insights into various aspects of movies, such as movie titles, production dates, genres, runtime minutes, director information, average ratings, number of votes, approval index, production budgets, domestic gross earnings, and worldwide gross earnings.

The dataset combines data scraped from Wikipedia, which includes details about movie titles, production dates, genres, runtime minutes, and director information, with data from The Numbers, a reliable source for box office statistics. Additionally, IMDb data is integrated to provide information on average ratings, number of votes, and other movie-related attributes.

With this dataset, users can analyze and explore trends in the film industry, assess the financial success of movies, identify popular genres, and investigate the relationship between average ratings and box office performance. Researchers, movie enthusiasts, and data analysts can leverage this dataset for various purposes, including data visualization, predictive modeling, and deeper understanding of the movie landscape.

Features: - Movie_title - Production_date - Genres - Runtime_minutes - Director_name (primaryName) - Director_professions (primaryProfession) - Director_birthYear - Director_deathYear - Movie_averageRating : refers to the average rating given by online users for a particular movie - Movie_numberOfVotes : refers to the number of votes given by online users for a particular movie - Approval_Index :is a normalized indicator (on scale 0-10) calculated by multiplying the logarithm of the number of votes by the average users rating. It provides a concise measure of a movie's overall popularity and approval among online viewers, penalizing both films that got too few reviews and blockbusters that got too many. - Production_budget ( $) - Domestic_gross ($) - Worldwide_gross ($)

Potential Applications:

Box office analysis: Analyze the relationship between production budgets, domestic and worldwide gross earnings, and profitability. Genre analysis: Identify the most popular genres based on movie counts and analyze their performance. Rating analysis: Explore the relationship between average ratings, number of votes, and financial success. Director analysis: Investigate the impact of directors on movie ratings and financial performance. Time-based analysis: Study movie trends over different production years and observe changes in production budgets, box office earnings, and genre preferences. By utilizing this dataset, users can gain valuable insights into the movie industry and uncover patterns that can inform decision-making, market research, and creative strategies.

Female moviegoers aged 18 to 34 years old represented ** percent of the audience of movies released in the first half of 2024 in the United States and Canada. The data shows that younger consumers went to the movies more often, as the audience share dropped sharply among viewers aged 35 years old and older.

The drive-in theater industry, while a niche market, is experiencing a resurgence driven by several factors. Nostalgia plays a significant role, with consumers seeking a unique and retro entertainment experience. The COVID-19 pandemic unexpectedly boosted the industry as drive-ins offered a safer, socially distanced alternative to traditional cinemas. This renewed interest, coupled with strategic investments in modernizing facilities—including improved sound systems, larger screens, and enhanced concessions—is fueling market growth. Furthermore, the appeal to families and younger generations seeking outdoor activities contributes to the industry's expansion. While competition from streaming services and traditional cinemas remains a challenge, drive-ins are leveraging their unique selling proposition of outdoor entertainment and community events to attract a wider audience. Assuming a current (2025) market size of $200 million and a CAGR of 5% (a reasonable estimate given the resurgence and niche nature), the market is projected to grow steadily over the next decade. This growth will be influenced by factors such as effective marketing campaigns targeting specific demographics, strategic partnerships with local businesses and event organizers, and further technological advancements enhancing the overall drive-in experience. Challenges include maintaining consistent attendance across seasons, managing land costs and operational expenses, and attracting and retaining qualified staff. However, the overall outlook for the drive-in theater industry is positive, with significant potential for further expansion and market penetration in the coming years.

The global movie theatre market is anticipated to rise from USD 674.52 million in 2025 to USD 1,233.02 million by 2033, growing at a 5.1% CAGR from 2025 to 2033. The expansion of the home entertainment sector, which includes streaming services and home theatre systems, is one of the primary factors influencing market growth. The market is also being driven by the development of new technologies, such as 3D and 4D projection, immersive experiences, and premium seating. Various market segments contribute to the overall revenue stream of the movie theatre industry. Based on cinema type, the multiplex theatres segment held the largest market share in 2025. Multiplex theatres offer a diverse range of movie options, comfortable seating, and advanced amenities, making them a preferred choice for moviegoers. The large screens segment dominated the market in 2025 in terms of screen size, providing an immersive and enhanced cinematic experience. Regionally, North America was the largest market for movie theatres in 2025, with the United States being a major contributor. The presence of numerous movie theatre chains, a large population base, and a strong movie-going culture drive the market in this region. This report provides an in-depth analysis of the global movie theater market, with detailed insights into market dynamics, key trends, competitive landscapes, and future growth opportunities. The report offers valuable insights for industry stakeholders, including market size estimates, growth projections, and region-specific analysis. It also examines the impact of technological advancements, changing consumer preferences, and the evolving regulatory environment on the market's trajectory. Key drivers for this market are: 1 Immersive Cinema Experiences IMAX Dolby Atmos2 Premium Seating Reclining Seats VIP Lounges3 Digital Content Distribution Streaming Services4 InTheater Dining Gourmet Concessions Restaurants. Potential restraints include: Increased adoption of advanced technologies Growing popularity of streaming services Rise in disposable income and leisure spending. Surge in demand for personalized movie experiences.

Employment statistics on the Movie Theaters industry in the US

This table contains 420 series, with data for years 1996/1997 - 2004/2005 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (12 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...), Type of venue (3 items: Total movie theatres and drive-ins; Movie theatres; Drive-ins), Summary characteristics (14 items: Number of theatres; Paid admissions; Average ticket prices; Number of screens; ...).

The global movie rating sites market is a dynamic and rapidly evolving sector, driven by the increasing consumption of online streaming services and the growing reliance on user reviews and professional critiques to inform viewing choices. The market, estimated at $2 billion in 2025, is projected to experience robust growth, fueled by factors such as the expanding reach of internet access, particularly in emerging markets, and the continued rise of mobile-first content consumption. Key market drivers include the escalating demand for credible and unbiased movie reviews to combat information overload and the need for personalized recommendations within the overwhelming variety of available content. The integration of advanced analytics and machine learning algorithms by major players further enhances the market's potential, offering more accurate and personalized recommendations to users. Segmentation within the market reveals a strong emphasis on user-generated content, reflecting the influence of peer reviews in shaping consumer decisions. However, the market also faces potential restraints such as the challenge of maintaining accuracy and impartiality in user ratings, as well as the increasing competition from social media platforms that offer informal yet influential movie discussions. The proliferation of niche movie rating platforms targeting specific genres or demographics also presents a challenge to the dominance of established players. The market's geographical distribution shows significant concentration in North America and Europe, reflecting the higher internet penetration and established movie-going culture in these regions. However, rapid growth is anticipated in Asia-Pacific regions, particularly in India and China, driven by the booming film industries and increasing smartphone usage. The competitive landscape is characterized by both established players like Rotten Tomatoes and IMDb, with significant brand recognition and extensive user bases, and emerging niche platforms targeting specific audience segments. The competitive dynamics will likely see increased investment in technology, data analytics, and marketing to attract and retain users in a crowded market. Future growth will depend heavily on the ability of platforms to adapt to evolving consumer preferences, leverage data effectively, and integrate seamlessly with other entertainment platforms. The focus on improving user experience and delivering personalized recommendations will be crucial for success.

During a survey conducted in the United States in April and May 2022, little more than one-third (** percent) of responding internet users whose household income stood below ** thousand U.S. dollars said they went to the movies either often or sometimes. Among respondents whose income surpassed 100 thousand dollars the combined share stood at ** percent. Moviegoers from the Northeast of the U.S. reported going to theaters more often than consumers from the Midwest in 2022.

users.csv User_id: Unique identifier of user Country_code: Country code where the user registered assets.csv Show_type: Type of content, whether the asset is a movie or an episode of a TV series Genre: Genre of content Running_miutes: Runtime of content (Playable number of minutes) Source_language: Production language of content Asset_id: Unique identifier of video content at the most granular level (a movie or an episode of a TV series) Season_id: Unique identifier of content at season level. This is only applicable to TV series Series_id: Unique identifier of content at series level. This is only applicable to TV series Studio_id: Unique identifier of production studio for the content plays.csv Platform: Platform of consumption Minutes_viewed : Total number of minutes viewed, rounded to the nearest integer (0 means less than 30 seconds) Demographics.csv Psychographics.csv The dataset identifies psychographic and demographic tags about some iflix users. Each user-tag pair has an associated confidence score (1 is the highest, and 0 is the lowest confidence). Each trait can have up to 3 levels, depending on its granularity. Some traits can be identified by only considering the first two levels. At the same time, there are others that make more sense when all the three levels are considered, e.g., ‘iflix Viewing Behaviour’ is a level 2 psychographic trait that only makes sense when it is looked at in combination with the level 3 traits corresponding to it (‘casual,’ ‘player’ and ‘addict’). These traits represent different levels of viewing behavior of iflix users. Casual users have less than five viewing days in a month, player users have 5 to 12 viewing days in a month, and people with an addiction have more than 12 viewing days in a month. Traits are available corresponding to a user_id in the dataset only if we have certain confidence that the user belongs to the trait. Column and Description Level_1: Identifies the first level of the trait (psychologic or demographic) Level_2: Identifies the second level of the trait (e.g., Music Lovers, Movies Lovers) Level_3 : Identifies the third level of the trait, if available/relevant (e.g. Malay Movies Lovers, Indonesian TV Fans) Confidence_score: Confidence in associating the said trait (level_1, level_2, level_3) with the user