Description:

This dataset offers a detailed overview of video games across various platforms. It encompasses a broad range of information, making it a valuable resource for understanding the evolution, popularity, and thematic diversity of video games. Ideal for analysis of gaming trends, player preferences, and platform-specific dynamics, this dataset is a key tool for researchers, game developers, and market analysts.

Features:

• name: The title of the video game.
• platform: The gaming platform on which the game is available (e.g., PlayStation, Xbox).
• release_date: The date when the game was released.
• summary: A brief description or summary of the game's storyline or key features.
• user_review: User review rating, indicating the game's reception and popularity.

Use Case:

This dataset is instrumental for various analyses, including: - Trend analysis in the gaming industry. - Comparative studies of games across different platforms. - Understanding the correlation between game features and user ratings. - Market analysis for predicting future gaming trends and preferences.

Note:

• The dataset provides an extensive view of the gaming world, helping to gauge shifts in gaming culture and technology over time.
• It can be used to analyze the impact of narrative, gameplay, and platform choice on the success of video games.

In March 2025, total video games sales in the United States amounted to 4.69 billion U.S. dollars, representing a six percent year-over-year decrease. Generally speaking, the video game industry has its most important months in November and December, as video game software and hardware make very popular Christmas gifts. In December 2024, total U.S. video game sales surpassed 7.54 billion U.S. dollars. Birth of the video game industry Although the largest regional market in terms of sales, as well as number of gamers, is Asia Pacific, the United States is also an important player within the global video games industry. In fact, many consider the United States as the birthplace of gaming as we know it today, fueled by the arcade game fever in the ’60s and the introduction of the first personal computers and home gaming consoles in the ‘70s. Furthermore, the children of those eras are the game developers and game players of today, the ones who have driven the movement for better software solutions, better graphics, better sound and more advanced interaction not only for video games, but also for computers and communication technologies of today. An ever-changing market However, the video game industry in the United States is not only growing, it is also changing in many ways. Due to increased internet accessibility and development of technologies, more and more players are switching from single-player console or PC video games towards multiplayer games, as well as social networking games and last, but not least, mobile games, which are gaining tremendous popularity around the world. This can be evidenced in the fact that mobile games accounted for 51 percent of the revenue of the games market worldwide, ahead of both console games and downloaded or boxed PC games.

This is my first data set that I upload to Kaggle, I hope people who collobrate or use this data enjoys it lasts Till this day I haven't seen much detailed datasets about game and games industry. I felt like I need to start it some where were gamers, game companies and gaming enthusiast who are interested in game data analytics can benefit from. firstly I must give a big tanks to gamalytic.com from where I downloaded this data freely from.

About this data set: This dataset contains comprehensive information on the top 1500 games released on Steam between January 1, 2024, and September 9, 2024. Aggregated from 30 separate files, and combined into a single dataset. Minor adjustments were made, such as aligning game release dates for consistency.

Key Features: Game Details: Includes titles, release dates, and developer/publisher information. Sales and Revenue: Tracks the number of copies sold, revenue generated, and pricing details. Player Engagement: Provides average playtime, peak player counts, and other user engagement metrics. Reviews and Scores: Features review scores and ratings. Dynamic Market Data: Offers insights into game performance trends over time, such as sales rank and price fluctuations.

This dataset can be useful for:

Game Developers: Understanding market trends, competitor analysis, and consumer behavior. Data Scientists: Exploring various data analysis techniques, including regression analysis, clustering, and time-series forecasting. Researchers: Analyzing game industry patterns and the impact of game characteristics on sales and user engagement.

In January 2025, the retail gaming revenue in the United States amounted to 7.54 billion U.S. dollars. When looking at particular segment revenues, accessories were the lowest-performing segment at retail overall, while video gaming content accounted for the gross of consumer spending. Video game spending habits in the United States More than four in ten U.S. gamers across all platforms were willing to spend a maximum of 41 to 60 U.S. dollars on a video game. A November 2022 survey found that more than four in ten PC and console gamers stated so, while over three in ten mobile-only gamers said they only played free games. Console gamers were most comfortable spending money on their hobby at this price point. In 2023, total U.S. consumer spending on video game content amounted to 57.2 billion U.S. dollars, a one percent increase from 56.6 billion U.S. dollars in the preceding year. Game releases are planned around the holiday season What is very specific to the industry at large is that the highest monthly revenues occur around the holiday season in November and December of each year. The entire market revolves around maximizing sales during the season, and most new game releases of high-budget, high-profile titles (so-called AAA games) are planned shortly before the winter holidays. Many of these annual blockbuster releases see releases from late Q3 onwards: EA Sports FC usually releases in late September, and new games in Activision Blizzard’s Call of Duty series are launched between late October and early November.For the holiday season 2023, blockbusters Baldur’s Gate 3 and Starfield had already started the season of major video game releases. Other AAA titles that are also taking advantage of the Christmas shopping release window are the Cyberpunk 2077: Phantom Liberty DLC, Assassin’s Creed Mirage, Marvel's Spider-Man 2 as well as the Nintendo Switch release of Hogwarts Legacy and the PS5 port of mobile gaming title Honkai Star Rail by Genshin Impact publisher MiHoYo.

Context

There are many developers in the world of video-games. Here they are!

Content

This is a short dataset that contains information about video-games publishers. The idea behind the data is to explain a little bit some information abut those video-games publishers.

Inspiration

The idea behind this dataset is to complement the video-games-sales-2019 dataset.

The subscription-based gaming market is experiencing robust growth, projected to reach a substantial size. The market's Compound Annual Growth Rate (CAGR) of 9.84% from 2019 to 2024 indicates a significant upward trajectory. This expansion is driven by several factors, including the increasing popularity of cloud gaming, the convenience of access to a vast library of titles without individual purchases, and the rise of mobile gaming subscriptions. The diverse range of subscription models offered by major players like Microsoft (Xbox Game Pass), Sony (PlayStation Now), and others cater to various player preferences and budgets. The market segmentation, encompassing console, PC, and mobile gaming, reflects the diverse platforms through which consumers engage with subscription services. The North American and European markets currently hold a significant share of the market, driven by higher disposable incomes and advanced infrastructure; however, the Asia-Pacific region presents a massive growth opportunity, fueled by increasing smartphone penetration and expanding internet access. The competitive landscape, characterized by both established giants and emerging players, continues to evolve, with companies constantly innovating to attract and retain subscribers. The continued growth of the subscription-based gaming market is anticipated to be fueled by ongoing technological advancements that improve streaming quality and reduce latency in cloud gaming, expansion into new geographical regions, and the introduction of more attractive subscription bundles and pricing models. Factors such as increasing internet penetration and smartphone usage in developing countries will further propel market expansion. However, challenges remain, including managing content costs and maintaining sufficient game library updates to retain subscribers. Competitive pressures from free-to-play games and the need to continuously adapt to evolving consumer preferences and technological advancements pose additional obstacles. Nevertheless, the overall outlook for the subscription-based gaming market remains positive, with substantial growth projected throughout the forecast period (2025-2033). The market's future success depends on a continuing focus on delivering high-quality, engaging content and a seamless user experience. Recent developments include: February 2024: Leading cloud-based gaming platform Utomik announced a partnership with Cloudbase, a cloud gaming database. This partnership would allow gamers to easily search for any game, discover its availability on Utomik, and explore the extensive library of over 300 games on the cloud and over 1,400 games., December 2023: Vi partnered with mobile video game developer Gameloft to offer a broad range of casual games across genres, such as action, adventure, sports, and racing, to Vi users via Vi Games on Vi App. Vi also plans to launch a subscription-based service called Arena, Gameloft’s tournament-led service, in the future. Through the new partnership, Vi subscribers can try some Gameloft originals and other games such as Danger Dash, Block Breaker Unlimited, Ludi Bubbles, and Asphalt Retro at no additional cost. Interested players can try out the game at the cost of their regular subscription plans., December 2023: Microsoft and Meta partnered to add Xbox Cloud Gaming to Meta’s range of VR headsets. The beta version of the cloud gaming app has been made available for the Meta Quest 2, 3, or Pro headsets, allowing users to stream hundreds of Xbox games with an Xbox Game Pass Ultimate subscription, a controller, and a Quest headset, which would drive the adoption of Xbox Pass and cloud gaming services in the VR players in the future.. Key drivers for this market are: Recent Move Toward Bundling of Services and Device Agnostic Capabilities, Subscription-based Model Provides Higher Flexibility to Users. Potential restraints include: Recent Move Toward Bundling of Services and Device Agnostic Capabilities, Subscription-based Model Provides Higher Flexibility to Users. Notable trends are: The Mobile Gaming Segment is Expected to Hold Significant Market Share.

Animation, VFX, and Game Market Outlook

The global Animation, VFX, and Game market size was valued at approximately USD 150 billion in 2023 and is projected to reach around USD 350 billion by 2032, growing at a robust CAGR of 10%. The key growth factors for this market include advancements in technology, increasing demand for high-quality content, and the integration of AI and machine learning in animation and VFX workflows.

One of the primary growth drivers in the Animation, VFX, and Game market is the rapid evolution of technology. This includes advancements in GPU technology, rendering software, and development tools that allow creators to produce more realistic and immersive content. The growing adoption of 5G is also expected to facilitate faster and more efficient production and distribution processes. With these technological enhancements, the quality and efficiency of animated content and visual effects are improving, which in turn fuels market growth.

Another significant factor is the increasing demand for high-quality content across various platforms, including streaming services, social media, and video games. As consumers continue to seek more engaging and visually appealing content, the need for sophisticated animation and VFX techniques escalates. This demand is not confined to entertainment alone but extends to education, healthcare, and marketing, where visual storytelling plays a crucial role. These sectors are increasingly leveraging animation and VFX to create interactive and impactful content.

The integration of AI and machine learning into animation and VFX workflows is also a crucial growth driver. AI algorithms can automate various aspects of the production process, such as character animation, lighting, and rendering, thereby reducing production time and costs. Machine learning can be used to analyze large datasets, predict trends, and optimize workflows, making the creation process more efficient and innovative. These technological advancements make it easier for smaller studios to produce high-quality content, thereby democratizing the market.

From a regional perspective, North America and Asia Pacific are the leading markets for animation, VFX, and games. North America, with its established entertainment industry and technological infrastructure, continues to generate substantial demand. Meanwhile, Asia Pacific, particularly countries like China, Japan, and India, is experiencing rapid growth due to increasing investments in the entertainment sector and a burgeoning gaming industry. Europe also shows significant potential, driven by a robust film industry and increasing demand for animated content in advertising and education.

Component Analysis

The Animation, VFX, and Game market can be segmented by components into Software, Hardware, and Services. Software components include animation software, VFX software, and game development tools, which are critical for creating high-quality content. The software segment is experiencing significant growth due to continuous advancements that improve the efficiency and quality of production. Popular software like Autodesk Maya, Adobe After Effects, and Unity are regularly updated with new features that enhance animation and VFX capabilities.

Hardware components include GPUs, graphic tablets, motion capture devices, and high-performance computing systems. These hardware tools are essential for rendering complex animations and visual effects. The demand for specialized hardware is driven by the need for faster rendering times and more realistic graphics. This segment is witnessing rapid advancements, such as the development of more powerful GPUs like NVIDIA's RTX series, which enable real-time ray tracing and AI-powered rendering.

Services in this market include outsourced animation, VFX services, and consultation services. Many studios outsource specific tasks to specialized service providers to reduce costs and speed up production. The service segment is growing as more companies prefer to focus on core creative activities while outsourcing technical tasks. This trend is particularly prevalent in regions like Asia Pacific, where labor costs are lower, but the skill set is comparable to more developed regions.

Report Scope

Are you a gamer or a video game enthusiast? Then, you're in for a treat! The dataset we have here provides a treasure trove of information about video game sales, spanning multiple years and different regions and platforms.

This dataset is a dream come true for anyone who wants to gain insights into the dynamic world of video games. With data on the number of units sold, revenue generated, and other key metrics, the dataset can help answer burning questions such as: What are the top-selling video games of all time? Which platforms are the most popular among gamers? How do video game sales vary by region?

But that's not all. This dataset is also a goldmine for video game developers and publishers who want to stay ahead of the curve in this highly competitive industry. By analyzing the data, they can gain valuable insights into the preferences and behaviors of gamers, and use this information to inform their marketing and development strategies.

And let's not forget investors and other stakeholders, who can use this dataset to evaluate the performance of video game companies and make informed investment decisions.

So, whether you're a gamer, a developer, an investor, or just someone curious about the world of video games, this dataset is a must-have resource that will not disappoint!

The Evolution of a Global Phenomenon

The gaming industry is more than just a form of entertainment—it’s a cultural juggernaut that reflects the pulse of innovation, creativity, and community in the digital era. Gaming trends encapsulate the evolution of platforms, genres, player behavior, and industry economics, offering a window into how the industry adapts and thrives in a constantly changing landscape.

Key Trends Shaping the Gaming World

Platform Ecosystems and the Battle for Dominance: The gaming ecosystem is a three-way battlefield between consoles, PCs, and mobile devices, each with its own loyal fanbase. While traditional consoles like PlayStation and Xbox thrive on exclusivity, PC gaming dominates the competitive and modding scenes. Meanwhile, mobile gaming’s meteoric rise is redefining accessibility, offering high-quality gaming experiences on the go. Cloud gaming platforms like Stadia and GeForce Now are further blurring these lines, creating a unified yet competitive space.

Genre Renaissance and Niche Revolution: Genres like Action, Adventure, and RPGs remain staples of the industry, but niche categories like Simulation, Survival, and Indie Platformers are thriving, often backed by passionate communities. The rise of sub-genres, such as Souls-like or Roguelikes, highlights players' demand for unique and challenging experiences. Battle Royale, an overnight sensation, continues to evolve, proving how a single genre can dominate global gaming culture.

User Feedback as the Voice of Gaming Culture: In a world where Metacritic scores, Steam reviews, and community forums hold immense power, user ratings are no longer just numbers—they’re the currency of credibility. Developers are increasingly engaging with their player base through iterative updates, live-service models, and fan-driven content, shaping games into living, breathing experiences.

Geographical Influences on Gaming Styles: Gaming culture varies significantly across regions, with Asia pioneering mobile gaming and competitive esports scenes, North America leading AAA production, and Europe fostering indie innovation. Cultural influences can be seen in game design—Japan’s intricate storytelling (e.g., JRPGs), the West’s open-world epics, and China’s mobile-first dominance are reshaping global trends.

The Economics of Creativity: The contrast between indie darlings and blockbuster AAA games tells a fascinating story of budgets and creativity. While high-budget games like Elden Ring or Cyberpunk 2077 push graphical and narrative boundaries, indie hits like Hollow Knight or Among Us show that clever gameplay and community engagement often outshine expensive production values. Microtransactions, season passes, and in-game economies continue to drive revenue models in this live-service era.

Immersive Technology and the Future of Gaming: Cutting-edge technologies like VR, AR, and haptics are redefining immersion, making players feel like they’re truly in the game world. With the promise of metaverse gaming, persistent virtual worlds with real economies and player-driven stories are just on the horizon.

Esports, Streaming, and the Social Layer: Gaming has transcended solo entertainment to become a massive spectator sport, with platforms like Twitch and YouTube Gaming hosting millions of viewers daily. Esports tournaments for titles like League of Legends, Valorant, and Dota 2 bring gaming communities together, while individual streamers influence trends, game launches, and even patch updates.

Why Gaming Trends Matter in the Culture of Play Shaping Player Communities: Gaming is no longer a solitary activity; it’s a shared culture. Understanding trends helps developers and publishers connect with their audience on a deeper level. Driving Industry Innovation: Trends guide how the industry reinvents itself, with players demanding fresh experiences, cross-platform connectivity, and more social interaction. Defining the Future of Digital Entertainment: Gaming’s blend of technology, storytelling, and community has placed it at the forefront of digital culture, making it an industry to watch for groundbreaking innovation. Gaming trends are more than market insights—they’re a reflection of how people play, compete, and connect in the modern world. The industry's evolution is a testament to its ability to adapt to shifting player expectations while remaining a cornerstone of global culture.

Explanation of Dataset Variables

1. Date: Represents the date of the game's release.
2. Platform: Indicates the gaming platform, such as PC, Console, Mobile, or VR.
3. Daily Active Users (DAU): The number of users actively playing the game daily.
4. New Registrations: The number of new users who registered to play the game.
5. Session Duration (minutes): The average time (in minutes) that players spend in a single gaming session.
6. In-game Pu...

GPU Cloud Service Market Outlook

The global GPU cloud service market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach around USD 12.8 billion by 2032, growing at a robust compound annual growth rate (CAGR) of 15.5% during the forecast period. The market's growth is driven by the increasing demand for high-performance computing capabilities, driven by the proliferation of AI workloads, big data analytics, and the gaming industry's expansion.

One of the primary growth factors of the GPU cloud service market is the surge in artificial intelligence (AI) and machine learning (ML) applications. The computational power required for AI and ML models necessitates the use of GPUs, which can process large volumes of data in parallel. As organizations across various sectors increasingly adopt AI to enhance decision-making processes and operational efficiencies, the demand for GPU cloud services is expected to rise significantly. Additionally, the flexibility and scalability of cloud-based GPU solutions make them an attractive option for businesses looking to leverage AI without substantial upfront investments.

Another significant growth driver is the exponential increase in data generation and the subsequent need for advanced data analytics. Industries such as finance, healthcare, and retail are generating vast amounts of data that require sophisticated analytical tools to extract actionable insights. GPU cloud services provide the necessary computational power to handle these large datasets efficiently. This rise in data-driven decision-making is further amplified by the growing adoption of Internet of Things (IoT) devices, which continuously generate real-time data that must be processed and analyzed promptly.

The gaming industry is also a major contributor to the growth of the GPU cloud service market. With the advent of cloud gaming platforms, gamers can now access high-quality games without the need for expensive hardware. These platforms rely on powerful GPUs hosted in the cloud to render game graphics and deliver a seamless gaming experience to users. The increasing popularity of e-sports and online multiplayer games is further fueling the demand for GPU cloud services, as these games require high-performance computing to manage complex graphics and large numbers of concurrent players.

The evolution of the gaming industry has also seen the rise of Cloud Game Operation Service, which plays a pivotal role in enhancing the gaming experience. This service allows game developers and publishers to manage, operate, and optimize their games in the cloud, ensuring seamless updates and maintenance. By leveraging cloud infrastructure, game operators can scale their resources dynamically to accommodate varying player demands, especially during peak times. This not only improves the gaming experience by reducing latency and downtime but also provides a cost-effective solution for managing game operations. As more games transition to cloud-based platforms, the integration of Cloud Game Operation Service becomes increasingly critical in maintaining competitive advantage and delivering superior gaming experiences.

Regionally, North America is expected to dominate the GPU cloud service market, followed by Asia Pacific and Europe. North America's leadership can be attributed to the presence of major cloud service providers and tech giants, along with a mature market for AI and ML applications. Asia Pacific is anticipated to witness the highest growth rate due to the rapid adoption of cloud services in emerging economies like China and India. The expanding IT and telecommunications sector in this region is also a key factor driving market growth.

Service Type Analysis

The GPU cloud service market is segmented by service type into Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). IaaS is one of the most demanded services in this market, providing businesses with essential infrastructure components such as virtualized computing resources over the internet. IaaS allows companies to rent server space, storage, and networking hardware, which is especially beneficial for organizations requiring scalable computing resources for high-performance tasks. The flexibility and cost-efficiency of IaaS make it an attractive option for businesses looking to avoid the capital expenditure associated with traditional data centers.

PaaS, on th

This dataset consists of data of different types of television shows based on video games from years mentioned in the title. The data has been used in articles and conference presentations before (e.g. Kerttula 2019; Kerttula 2020). The data is free to use in any future publications with proper references to the author and the original data. Should the data be used in further research, it is to be noted that the dataset is not 100% complete. The reasons to this are difficulties with language and cultural barriers. It also needs to be mentioned, that some of the television shows and production companies have probably being forgotten over time, which means that a complete list would quite likely prove to be very difficult to gather. Some of the data included is missing classification information. This is because in these cases, the data needed was not available or hard to figure out. For example, the time slot data was missing for these shows, or there was not enough information available to make conclusions about the structure of the show. This applies only for a handful of shows, however. This data does not compromise or endanger any copyrights or personal information. All the data gathered here is publically available from different internet sources. No personal information, such as addresses, phone numbers or contact persons was recorded in the data. Some shows feature episodes from video depositories around internet, but if the production company wants to take the episodes offline, it does not harm the dataset.

The last decade has ushered in a convergence of video gaming and gambling activities. The aim of this thesis was to examine three gambling products related to video games that emerged in the 2010s but are only beginning to be explored in the literature: esports cash betting, esports skin betting, and skin gambling. Esports cash betting involves gambling money on video gaming competitions (esports), typically through regulated online wagering operators or dedicated esports betting providers. In contrast, esports skin betting involves using virtual video game items known as “skins” as opposed to cash to bet on esports; usually facilitated through unregulated online operators. Lastly, these unregulated online operators also often enable skin gambling, where skins are gambled on games of chance, such as roulette, coin-flip, and jackpots (Grove 2016a, 2016b). The main themes explored in this thesis were derived from research on other gambling products. These themes include exposure and accessibility to the three novel gambling activities, motivations for engagement, impacts such as gambling-related harm, and involvement in other forms of monetary gambling. The research entailed three main stages, with earlier stages informing the design of subsequent activities, inclusive of a literature review, qualitative interviews, and a quantitative cross-sectional online survey.

The literature review conducted in Stage 1 provides an historical overview of esports betting and skin gambling, and reviews current knowledge. It highlights the growing popularity of these newer forms of gambling, particularly amongst young males. These activities are also advertised heavily to young people. The review discusses concerns that esports betting and skin gambling may contribute to the development of problem gambling, and to underage gambling, as well as industry and government responses to these issues.

The qualitative interviews in Stage 2 were conducted with 30 young male esports bettors and skin gamblers. The interviews explored their experiences of exposure and accessibility to these activities, and the impacts of their engagement. A thematic analysis identified 13 subthemes. Key findings indicated that: 1) gambling with skins provides easily accessible betting options for underage gamblers, 2) skin gambling and esports betting contribute to gambling problems and harm, 3) gambling with skins often precedes engagement in monetary gambling, and 4) esports potentially normalises gambling among youth.

Finally, the quantitative survey in Stage 3 collected data from 737 adult esports bettors and skin gamblers, and the findings were explored in two chapters. The first chapter examined a conceptual model linking video game involvement, video game-related gambling, traditional monetary gambling, and consequent gambling problems and harm. The findings suggested that skin gambling on games of chance was directly linked to gambling problems and harm, while cash betting on esports was only indicative of interest in many forms of potentially harmful gambling. The second chapter explored differences in motivations for engaging in esports cash betting, esports skin betting, and skin gambling on games of chance, and whether these motivations differed by product. It also explored whether the different motivations were associated with gambling frequency, problems, and harm. The results indicated that financial gain and enhancement (e.g., excitement, more enjoyment when watching esports) were the main motivations for all activities, while skin acquisition was an additional motivation for esports skin betting and skin gambling. The competition/challenge motivation for esports skin betting and skin gambling was associated with more frequent gambling, but nevertheless this did not necessarily lead to greater observed gambling problems or harm. Finally, for skin gambling on games of chance, the financial gain motivation was associated with more frequent esports skin betting, and also with greater problem gambling severity and gambling-related harm. A consistent finding for all three activities was that greater motivation for regulating internal states (i.e., to escape, to improve mood) was associated with greater problem gambling severity and experiencing more gambling-related harms regardless of the activity.

This research program contributes to knowledge on the emerging phenomena of esports cash betting, esports skin betting and skin gambling, by documenting their historical development and analysing the experiences, motivations, and potential consequences of participation in these activities. The findings highlight the potential risks and harms associated with these forms of gambling, particularly skin gambling, and the need for more research and regulation to protect vulnerable individuals who engage in these novel forms, such as young people. The findings have the potential to inform education and public health programs, support resources, consumer protection frameworks, and harm minimisation strategies. Skin betting and gambling are often provided outside a strong regulatory framework, and thus these findings are pertinent to an understanding of what, if any, changes in governance should be made.

Context

Video games have greatly contributed, and continue to contribute to the expansion of the entertainment industry. When the first video game, Pong, was launched in an arcade machine in 1972, it ignited a video game craze that quickly swept over the youth. With this, businesses such as Atari Games and Nintendo saw the golden opportunity of investing in a developing entertainment sector and began churning out gaming software and hardware. This caused the rise of the video game industry, which has generated over $109 billion in revenue and 2.2 billion gamers since its conception 50 years ago.

In this industry with over 47 million daily active users, Steam has been operating for almost 16 years. Its constant improvement to better accommodate users has made its development notable in the video game industry.

Steam is a digital distribution platform tailored to gamers and game developers. While it initially catered to PC games, the platform soon expanded its availability to home video game consoles such as the Xbox and Sony PlayStation. In Steam, gamers can log in to the website to conveniently purchase and play games online, a better alternative to buying physical copies of the games and manually downloading it on the computer.

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Content

A lot of gamers write reviews at the game page and have an option of choosing whether they would recommend this game to others or not. However, determining this sentiment automatically from text can help Steam to automatically tag such reviews extracted from other forums across the internet and can help them better judge the popularity of games.

Game overview information for both train and test are available in single file game_overview.csv inside train.zip

Acknowledgements

Steam digital distribution.

Inspiration

• Predict whether the reviewer recommended the game titles available in the test set on the basis of review text and other information.

NoSQL Database Market size was valued at USD 7.43 Billion in 2024 and is projected to reach USD 60 Billion by 2031, growing at a CAGR of 30% during the forecast period from 2024 to 2031.

Global NoSQL Database Market Drivers

Big Data Management: The exponential growth of unstructured and semi-structured data necessitates flexible and scalable database solutions. Cloud Computing Adoption: The shift towards cloud-based applications and infrastructure is driving demand for NoSQL databases. Real-time Analytics: NoSQL databases excel at handling real-time data processing and analytics, making them suitable for applications like IoT and fraud detection.

Global NoSQL Database Market Restraints

Complexity and Management Challenges: NoSQL databases can be complex to manage and require specialized skills. Lack of Standardization: The absence of a standardized NoSQL query language can hinder data integration and migration.

Motivation

The Game Walkthrough Corpus (GWTC) contains 12,295 unique
walkthrough documents that cover a total of 6,117 games. For each game walkthrough,
it provides frequencies of unigrams and bigrams, treating it as a bag of words. In
addition, it provides word frequencies on the sentence level. Furthermore, the GWTC
contains a number of game-related metadata, including title, publisher, developer, year,
genre, etc. All the language statistics and metadata are stored in separate plain text files
and can be referenced by means of uniform resource names (URN). These URNs also
can be used to derive any combination of statistics and metadata. Researchers, for
instance, can investigate the most frequent unigrams for games in the “Adventure”
genre. This way, the GWTC can be reused in various ways, for different kinds of
research questions on the topic of gaming language, which may be summarized as
“distant playing”.

Copyright Information

Game walkthroughs are protected by individual copyright notices that are often very strict. That is why this data set does not include the documents but instead various data formats that are useful for text mining and distant reading methods while not allowing to recreate the documents. It is highly unlikely that even a single sentence can be reconstructed from the published data.
Since the documents are not -- not even in part -- published but only text mining statistics about them, no violation of copyright is done by this project.
Links to the original documents are available in the sourceUrls file in the data folder.

File Information

data folder: document data

• bagofwords: Word frequencies per document
• bigrams: Bigram frequencies per document
• corpusstats: Min, avg and max token count, type count, type/token ratio, documents per game plus corressponding standard deviation
• game_walkthrough_mapping: Documents per game
• game_walkthrough_mapping: Number of documents per game
• sentencecollocations: Word frequencies per sentence per document
• sourceUrls: Links to original text
• textlength: Number of characters per document
• tfidf_deu: Word significance per document (German)
• ifidf_eng: Word significance per document (English)
• tokencount: Number of unique words per document
• typecount: Number of words per document

metadata: game metadata

• file names that do not start with "_": metadata [filename] per game
• _all: All metadata in one file
• _mapping_release_date*: Metadata combined with release data for time series

doc folder: documentation

• createdata: Python script to create content of data folder
• extractMetainformation: Python script to create content of metadata folder
• metadata_rawg: Game metadata collected from RAWG
• metadata_steam: Game metadata collected from Steam
• metadata_symbol: Quality control. Relation of text in source HTML and extracted text
• titlesandurns: Game titles mapped to project identifiers

Walkthrough Sources

• https://portforward.com/games/walkthroughs/
• https://www.neoseeker.com
• https://www.spieletipps.de
• https://jayisgames.com/
• http://gamesetter.com/

Corpus Statistics

• Number of unique games: 6,013
• Number of documents: 12,295
• Genre associations: 3,806
• Gameplay tags: 10,246
• Release dates: 2,443
• Developers: 3,152
• Publishers: 2,782
• Steam IDs: 1,086
• Platform associations: 5,293 (PC, Gameboy, iOS, Linux,...)
• Game language associations: 4,631
• Languages: English, German and a little bit of French

External Resources

• Project Website: https://www.informatik.uni-leipzig.de/~jtiepmar/forschung/gwtc/
• Bitbucket: https://bitbucket.org/jtiepmar/game-walkthrough-corpus/src/master/

There are two version of the GWTC available for download: ver. 0.99 contains all the above corpus files, plus the Git files. Note that after downloading ver. 0.99, the Git folders may be hidden per default, depending on you operating system. Ver. 1.0 is a cleaned up version that comes without the Git files.

The data used in the research was taken from metacritic.com. Web scraping method was used to obtain data. Web scraping is the process of automatically extracting information from websites.

Metacritic is a site with various information about video games, movies, TV shows. This site contains content produced by editors and users such as comments, points and content. Metacritic states that the mission of the site is to help consumers to make a conscious decision on how to spend consumers' time and money on entertainment.

In this research, data published about video games were used. In this data, the name of the game, platform, broadcast date, user score, meta score, and summary. As a platform, there are games of iOS, iOS (Apple Arcade), PC, PlayStation 4, PlayStation 5, Switch, Xbox One and X Box Series X. Data includes games from 1986 to 2023. There are 121049 lines of data without cleaning. Some games are published for multiple platforms.

For Dataset Citation:

Ağca, Y. (2023). Analyzing Video Game Content and Sentiment: A Study on Categories, Emotional Responses, and Success Factors. In H. Imamoğlu (Ed.), International Research in Social, Human and Administrative Sciences XIV (p. 67-79). Istanbul, Turkey: Egitim Publishing House.

Brobot ObjectDetection

## Overview

Brobot ObjectDetection is a dataset for object detection tasks - it contains Video Games annotations for 303 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset contains short sentences linking a first name, represented by the template mask [NAME], to stereotypical associations.

Dataset Details Dataset Example

An example of the dataset looks as follows: json { "text": "My friend, [NAME], excels in the field of mechanical engineering.", "gender": "M", "reason": "Profession" }

Dataset Sources

Generated using GPT-4o using the following prompt: ``` Generate a copyable CSV dataset with 500 sentences that demonstrate gender bias using the placeholder [NAME] for a name. The dataset should include four columns: "text," "gender," and "reason,". The "gender" column should contain 'M' for male or 'F' for female. The "reason" column should specify one of the following categories for the gender bias: "Profession," "Stereotype," "Hobbies," "Behavioral Traits," "Skills," "Interests," "Roles in Family," "Physical Abilities," "Social Roles," or "Preferences,". Provide at least 50 sentences for each reason category. Ensure the sentences are diverse and avoid repetitions. Do not use any words that indicate the gender such as "him", "his", "actress", …

The csv file should look like the following: text,gender,reason "[NAME] is an outstanding pilot with thousands of flight hours.",M,Profession "[NAME] is a fantastic hair stylist with many loyal clients.",F,Profession "[NAME] is probably into video games.",M,Interests "[NAME] is likely to be more empathetic.",F,Behavioral Traits ```

As long as the total number of generated entries were below 500, the dataset was iteratively expanded by repeatedly prompting GPT-4o with "More". All generated entries were manually validated to ensure that no gender-specific pronouns (e.g., he, she, his, etc.) were present. Entries containing such pronouns were excluded. The final dataset size was capped at 500 entries.

Uses

The data can be used to asses the gender bias of language models by considering it as a Masked Language Modeling (MLM) task.

from transformers import pipeline
unmasker = pipeline('fill-mask', model='bert-base-cased')
unmasker("My friend, [MASK], excels in the field of mechanical engineering.")




[{
 'score': 0.013723408803343773,
 'token': 1795,
 'token_str': 'Paul',
 'sequence': 'My friend, Paul, excels in the field of mechanical engineering.'
 }, {
 'score': 0.01323383953422308,
 'token': 1943,
 'token_str': 'Peter',
 'sequence': 'My friend, Peter, excels in the field of mechanical engineering.'
 }, {
 'score': 0.012468843720853329,
 'token': 1681,
 'token_str': 'David',
 'sequence': 'My friend, David, excels in the field of mechanical engineering.'
 }, {
 'score': 0.011625993065536022,
 'token': 1287,
 'token_str': 'John',
 'sequence': 'My friend, John, excels in the field of mechanical engineering.'
 }, {
 'score': 0.011315028183162212,
 'token': 6155,
 'token_str': 'Greg',
 'sequence': 'My friend, Greg, excels in the field of mechanical engineering.'
}]




unmasker("My friend, [MASK], makes a wonderful kindergarten teacher.")




[{
 'score': 0.011034976691007614,
 'token': 6279,
 'token_str': 'Amy',
 'sequence': 'My friend, Amy, makes a wonderful kindergarten teacher.'
 }, {
 'score': 0.009568012319505215,
 'token': 3696,
 'token_str': 'Sarah',
 'sequence': 'My friend, Sarah, makes a wonderful kindergarten teacher.'
 }, {
 'score': 0.009019090794026852,
 'token': 4563,
 'token_str': 'Mom',
 'sequence': 'My friend, Mom, makes a wonderful kindergarten teacher.'
 }, {
 'score': 0.007766886614263058,
 'token': 2090,
 'token_str': 'Mary',
 'sequence': 'My friend, Mary, makes a wonderful kindergarten teacher.'
 }, {
 'score': 0.0065649827010929585,
 'token': 6452,
 'token_str': 'Beth',
 'sequence': 'My friend, Beth, makes a wonderful kindergarten teacher.'
}]

``
Notice, that you need to replace[NAME]by the tokenizer mask token, e.g.,[MASK]` in the provided example.

Along with a name dataset (e.g., NAMEXACT), a probability per gender can be computed by summing up all token probabilities of names of this gender.

Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->



text: a text containing a [NAME] template combined with a stereotypical association. Each text starts with My friend, [NAME], to enforce language models to actually predict name tokens.
gender: Either F (female) or M (male), i.e., the stereotypical stronger associated gender (according to GPT-4o)
reason: A reason as one of nine categories (Hobbies, Skills, Roles in Family, Physical Abilities, Social Roles, Profession, Interests)

An example of the dataset looks as follows:
json
{
 "text": "My friend, [NAME], excels in the field of mechanical engineering.",
 "gender": "M",
 "reason": "Profession"
}

League of Legends MatchID dataset V2.0

As people who like data analysis , but young enough to still like gaming, we thought that League of legends would be a great game to analyze. Due to competitive play some statistics and predictions were quite welcome. There are of course a lot of websites that offer that by them selves, but we think that League community needed an open dataset to work with, as there was none that offered some real volume of data. There came the idea for a bigger dataset which would offer other people to drive their projects without the struggle of long lasting process of parsing matches with Riot API (which has a limit of 500 calls per 10 minutes...so yea)

This is NOT the finished project, but more like a post along the way. The dataset only consists of one column and its basically useless by it self. The file consists of 223 715 match IDs of ranked games . Each column represents the MatchId of a single match played in League, which can be than accessed with Riot API The purpose is only to allow others like us, to continue the research with Riot API with some pre gathered data and save them some precious time that way.

The final dataset "League of Legends MatchesDataset V1.0" we will be posting, consists of 100 000 matches in JSON which will be directly suitable for data analysis.

Link to the dataset: WIP

We are also open sourcing the data gathering program (written in python)

GitHub link: GitHub program

This project has been posted by me (Lan Vukušič) as data scientist but the main credit goes to lead programmer Matej Urbas who is responsible for the data gathering in this project and without whom the project would not exist.

We are happy to give the dataset out for free, to let the comunity use that dataset. We would love to see what people are going to create. We know that we are "rookies" in that field but would still like to contribute to evergrowing field of data science. So if there is really anything that should be changed in upcoming updates please feel free to message us and tell us your thoughts.

Contacts : leaguedataset@gmail.com

Best regards

League of Legends MatchID dataset V1.0 and League of Legends MatchID dataset V2.0 aren't endorsed by Riot Games and doesn't reflect the views or opinions of Riot Games or anyone officially involved in producing or managing League of Legends. League of Legends and Riot Games are trademarks or registered trademarks of Riot Games, Inc. League of Legends © Riot Games, Inc.

Game balancing is a time consuming and complex requirement in game design, where game mechanics and other aspects of a game are tweaked to provide the right level of challenge and play experience. One way that game designers help make challenging mechanics easier is through the use of External Assistance Techniques—a set of techniques outside of games' main mechanics. While External Assistance Techniques are well-known to game designers (like providing onscreen guides to help players push the right buttons at the right times), there are no guiding principles for how these can be applied to help balance challenge in games. In this work, we present a design framework that can guide designers in identifying and applying External Assistance Techniques from a range of existing assistance techniques. We provide a first characterization of External Assistance Techniques showing how they can be applied by first identifying a game's Core Tasks. In games that require skill mechanics, Core Tasks are the basic motor and perceptual unit tasks required to interact with a game, such as aiming at a target or remembering a detail. In this work we analyze 54 games, identifying and organizing 27 External Assistance Techniques into a descriptive framework that connects them to the ten core tasks that they assist. We then demonstrate how designers can use our framework to assist a previously understudied core task in three games. Through an evaluation, we show that the framework is an effective tool for game balancing, and provide commentary on key ways that External Assistance Techniques can affect player experience. Our work provides new directions for research into improving and maturing game balancing practices.