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AI Market In Media And Entertainment Industry Size 2024-2028

The AI market in media and entertainment industry size is forecast to increase by USD 30.73 billion at a CAGR of 26.4% between 2023 and 2028. The market is experiencing significant growth, driven by the usage of multimodal AI to enhance consumer experience, analyze audience behavior, and automate content production. Multimodal AI, which combines text, speech, and visual data, is revolutionizing media and entertainment by enabling personalized recommendations, real-time sentiment analysis, and advanced content creation. Additionally, the utilization of blockchain technology is gaining traction in the industry, offering secure and transparent data sharing, and ensuring data privacy and security. Furthermore, the reliance on external sources of data to train AI models is a key trend, as media and entertainment companies seek to leverage diverse datasets to improve their offerings and stay competitive. These factors are expected to fuel market growth in the coming years.

What will the size of the market be during the forecast period?

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Artificial Intelligence (AI) is revolutionizing the media and entertainment industry by enhancing various applications, including game play, fake story recognition, plagiarism detection, production planning, talent discovery, and virtual creation. AI's integration in media and entertainment is enabling high-definition graphics, real-time virtual worlds, and internet video streaming on Ott platforms. In the gaming sector, AI is used to create intelligent opponents, personalize gameplay experiences, and analyze player behavior for sales and marketing purposes. Social media platforms leverage AI and Machine Learning (ML) for natural language processing to provide personalized content recommendations. AI is also transforming sports analysis by generating live footage and identifying patterns to enhance the online gaming experience. Overall, AI is a game-changer in the media and entertainment industry, offering innovative solutions in content creation, distribution, and consumption. Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

Further, AI-powered rendering engines can create lifelike visuals by analyzing data from real-world environments and applying it to virtual creations. This not only enhances the viewing experience for consumers but also reduces production costs by allowing for more efficient and cost-effective production. AI is also being used to improve the online gaming experience. Real-time virtual worlds can be created using AI, allowing players to interact with each other and their environment in a better way. AI-generated live footage is also being used to enhance sports analysis, providing more accurate and detailed information to broadcasters and fans. In the realm of sales and marketing, AI is being used to analyze consumer behavior and preferences to create targeted marketing campaigns.

AI-powered chatbots can interact with customers, providing personalized recommendations and support. Additionally, AI can be used to analyze social media trends and identify potential marketing opportunities. In conclusion, AI is transforming the media and entertainment industry in numerous ways, from gameplay and talent discovery to high-definition graphics and sales and marketing. As AI and ML technologies continue to advance, we can expect to see even more innovative applications in this industry.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Technology

  Machine learning
  Computer vision
  Speech recognition


End-user

  Media companies
  Gaming industry
  Advertising agencies
  Film production houses


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  South America



  Middle East and Africa

By Technology Insights

The machine learning segment is estimated to witness significant growth during the forecast period. The media and entertainment industry has witnessed significant advancements with the integration of artificial intelligence (AI) and machine learning (ML) technologies. ML, in particular, has been instrumental in revolutionizing video data management and analysis. One illustration of this trend is the latest developments in object storage solutions, such as those provided by Wasabi Technologies. These solutions incorporate AI and ML capabilities for automated tagging of video data, facilitating efficient storage in S3-compatible object storage systems.

Market Overview:

The United States social media analytics market size is projected to exhibit a growth rate (CAGR) of 18.30% during 2025-2033. The increasing utilization of social media by users, rising emphasis on personalized marketing strategies, the widespread integration of artificial intelligence (AI) and machine learning (ML), and the burgeoning awareness about the importance of customer feedback represent some of the key factors driving the market.

Social media analytics refers to the process of gathering, analyzing, and interpreting data from social media platforms to understand online interactions and trends. They combine advanced analytics techniques, like text analysis and sentiment analysis, with user engagement metrics to provide insights into social media behavior. Social media analytics utilize algorithms, artificial intelligence (AI), and machine learning (ML) to process vast amounts of unstructured social media data. They include various types, such as descriptive, diagnostic, predictive, and prescriptive analysis, designed to manage large data volumes from various platforms. Social media analytics are utilized in various applications, including market research, customer service, public relations, sentiment analysis, trend analysis, competitive analysis, influencer identification, brand monitoring, campaign performance, and content optimization. They aid in enhancing customer insights, improving marketing strategies, providing real-time feedback, increasing return on investment (ROI), supporting crisis management, tracking audience engagement, and managing brand reputation. Furthermore, social media analytics are known for their data-driven decision-making, cost-effectiveness, scalability, versatility, accessibility, real-time analysis, user-friendliness, customizability, and comprehensive data visualization.

United States Social Media Analytics Market Trends:

The increasing utilization of social media by users, leading to the demand for advanced analytics tools capable of handling large and complex datasets, is fostering the market growth. Besides this, the rising emphasis on personalized marketing strategies, as companies leverage social media analytics to tailor their marketing efforts, is providing a thrust to the market growth. Along with this, the widespread integration of artificial intelligence (AI) and machine learning (ML) in social media analytics tools, enabling more sophisticated data processing and insight generation, is creating a positive outlook for the market growth. In line with this, the growing adoption of technologies that facilitate the analysis of unstructured data, sentiment analysis, and predictive modeling, providing businesses with actionable insights to form their strategies, is favoring the market growth. Apart from this, the burgeoning awareness about the importance of customer feedback in shaping business strategies is enhancing the market growth. Furthermore, the increasing adoption of social media analytics tools by companies to monitor customer opinions and feedback in real-time, allowing them to respond to consumer needs and market changes quickly, is acting as a growth-inducing factor. Along with this, the heightened investment in digital marketing, as businesses allocate more resources to online platforms, prompting the need for robust analytics tools, is providing a thrust to the market growth. In addition to this, the rising integration of social media analytics with other business intelligence tools, providing a more holistic view of the customer's journey, is offering lucrative growth opportunities for the market.

United States Social Media Analytics Market Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for 2025-2033. Our report has categorized the market based on component, deployment mode, organization size, application, and end user.

Component Insights:

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• Solutions
• Services
  

The report has provided a detailed breakup and analysis of the market based on the component. This includes solutions and services.

Deployment Mode Insights:

• On-premises
• Cloud-based
  

A detailed breakup and analysis of the market based on deployment mode have also been provided in the report. This includes on-premises and cloud-based.

Organization Size Insights:

• Small and Medium-sized Enterprises
• Large Enterprises
  

The report has provided a detailed breakup and analysis of the market based on the organization size. This includes small and medium-sized enterprises and large enterprises.

Application Insights:

• Customer Segmentation and Targeting
• Competitor Benchmarking
• Multichannel Campaign Management
• Customer Behavioral Analysis
• Marketing Management
  

A detailed breakup and analysis of the market based on application have also been provided in the report. This includes customer segmentation and targeting, competitor benchmarking, multichannel campaign management, customer behavioral analysis, and marketing management.

End User Insights:

• BFSI
• Media and Entertainment
• Travel and Hospitality
• IT and Telecom
• Retail
• Healthcare
• Others
  

The report has provided a detailed breakup and analysis of the market based on the end user. This includes BFSI, media and entertainment, travel and hospitality, IT and telecom, retail, healthcare, and others.

Regional Insights:

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• Northeast
• Midwest
• South
• West
  

The report has also provided a comprehensive analysis of all the major regional markets, which include the Northeast, Midwest, South, and West.

Competitive Landscape:

The market research report has also provided a comprehensive analysis of the competitive landscape in the market. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

United States Social Media Analytics Market Report Coverage:

The global market for Artificial Intelligence (AI) in Media and Entertainment is projected to grow from $24.13 billion in 2022 to $60.13 billion by 2029, at a CAGR of 12.2%. The market growth is attributed to the rising demand for AI solutions to automate tasks, improve efficiency, and enhance customer experiences in the media and entertainment industry. Additionally, the growing adoption of cloud computing, the increasing use of AI in video and image processing, and the rising popularity of virtual and augmented reality (VR/AR) are driving market expansion. Key trends in the AI in Media and Entertainment market include the integration of AI in content production, distribution, and consumption. AI powers personalized recommendations, automated content moderation, and enhanced search and discovery capabilities. Furthermore, AI is used to develop new interactive entertainment experiences, such as virtual assistants and virtual reality games. The adoption of AI in the media and entertainment industry is expected to continue to rise, driven by the need for cost-effective, automated, and personalized solutions.

Global Artificial Intelligence in Marketing market size is expected to grow from $20.23 Bn in 2023 to $193.28 Bn by 2032, at a CAGR of 28.50% from 2024-2032

Base Year 2023 Forecast Period 2024-2028 Market Growth X.XX%*

The generative AI media software market is experiencing significant growth, driven by advancements in artificial intelligence and machine learning. This market is valued at XXX million in 2025 and is projected to reach XXX million by 2033, with a CAGR of XX%. The key growth drivers include increased demand for personalized media content, automated media production, and enhanced user engagement. Additionally, the convergence of AI with other technologies, such as virtual reality and augmented reality, is creating new opportunities for media creation and distribution. The generative AI media software market is segmented by application, type, and region. The major applications include personal media, corporate media, and government media. The types of generative AI media software include voice media, text media, and image media. The market is geographically distributed across North America, South America, Europe, Middle East & Africa, and Asia Pacific. The prominent companies in this market include OpenAI, Google, Jasper, Tiama, IBM, iFlyTek, Brainasoft, Brighterion, Alibaba, TikTok, Tencent, Baidu, Perfect World, Kingsoft Office, Visual China Group, and KunLun. The market is highly competitive, with established players investing in research and development to gain a competitive edge.

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Cloud Artificial Intelligence (AI) Market Size 2024-2028

The cloud artificial intelligence (ai) market size is forecast to increase by USD 12.61 billion at a CAGR of 24.1% between 2023 and 2028.

The market is experiencing significant growth, driven by the emergence of technologically advanced devices and the increasing adoption of 5G and mobile penetration. These factors enable the integration of AI technologies into various applications, leading to improved efficiency and productivity. However, the market also faces challenges from open-source platforms, which offer free AI solutions, making it difficult for market players to compete on price. Despite this, the market is expected to continue its growth trajectory, driven by the increasing demand for AI solutions in various industries, including healthcare, finance, and retail. Organizations are leveraging cloud-based AI solutions to gain insights from their data, automate processes, and enhance customer experiences.The market analysis report provides a comprehensive overview of these trends and challenges, offering valuable insights for stakeholders looking to capitalize on the growth opportunities In the cloud AI market.

What will be the Size of the Cloud Artificial Intelligence (AI) Market During the Forecast Period?

Request Free SampleThe market is experiencing robust growth, driven by the increasing adoption of machine learning (ML), deep learning, neural networks, and generative AI technologies. These advanced algorithms are revolutionizing various industries by emulating human intelligence in speech recognition, digital media, diagnostics, cybersecurity, and business decision-making. Hyperscale cloud platforms are becoming the preferred infrastructure for AI applications due to their ability to handle massive data processing requirements. Cloud AI solutions are transforming IT services by automating routine tasks, enhancing data analytics, and improving human capital management. They offer significant cost savings by eliminating the need for expensive hardware and maintenance. Moreover, AI-driven cloud management and data management solutions enable predictive analytics, personalization, productivity, and security enhancements.In addition, AI is playing a pivotal role in threat detection and cybersecurity, ensuring business continuity and data protection. Overall, the cloud AI market is poised for exponential growth, as organizations continue to leverage AI to gain a competitive edge In their respective industries.

How is this Cloud Artificial Intelligence (AI) Industry segmented and which is the largest segment?

The cloud artificial intelligence (ai) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. ComponentSoftwareServicesGeographyNorth AmericaUSEuropeGermanyUKAPACChinaJapanSouth AmericaMiddle East and Africa

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

Artificial Intelligence (AI) software replicates human learning and behavior, revolutionizing various business sectors. AI development involves creating new software or enhancing existing solutions to deliver analytics results and trigger actions based on them. Applications of AI include automating business processes, personalizing services, and generating industry-specific insights. The digitization trend has driven industrial transformations, with healthcare being a prime example. According to BDO's Healthcare Digital Transformation Survey, 93% of US healthcare organizations adopted digital transformation strategies in 2021, integrating AI, computing, and enterprise resource planning software. AI functionality encompasses speech recognition, machine learning (ML), deep learning, neural networks, generative AI, automation, decision-making, and more.Hyperscale cloud platforms, IT services, infrastructure, data analytics, human capital management, cost savings, cloud management, data management, predictive analytics, personalization, productivity, security, threat detection, integration, talent gap, and chatbots are significant AI applications. AI tools process data, power business intelligence, and enable lower costs through ML-based models and GPUs. Enterprise datacenters, virtualization, public clouds, private clouds, and hybrid cloud solutions leverage AI for non-repetitive tasks. AI streamlines workloads, automates repetitive tasks, monitors and manages IT infrastructure, and offers dynamic cloud services. AI is transforming industries, from retail inventory management to financial organizations, providing competitive advantages through cost savings and improved decision-making capabilities.

Get a glance at the Cloud Artificial Intelligence (AI) Industry repo

General Description

This dataset comprises 4,038 tweets in Spanish, related to discussions about artificial intelligence (AI), and was created and utilized in the publication "Enhancing Sentiment Analysis on Social Media: Integrating Text and Metadata for Refined Insights," (10.1109/IE61493.2024.10599899) presented at the 20th International Conference on Intelligent Environments. It is designed to support research on public perception, sentiment, and engagement with AI topics on social media from a Spanish-speaking perspective. Each entry includes detailed annotations covering sentiment analysis, user engagement metrics, and user profile characteristics, among others.

Data Collection Method

Tweets were gathered through the Twitter API v1.1 by targeting keywords and hashtags associated with artificial intelligence, focusing specifically on content in Spanish. The dataset captures a wide array of discussions, offering a holistic view of the Spanish-speaking public's sentiment towards AI.

Dataset Content

• ID: A unique identifier for each tweet.
• text: The textual content of the tweet. It is a string with a maximum allowed length of 280 characters.
• polarity: The tweet's sentiment polarity (e.g., Positive, Negative, Neutral).
• favorite_count: Indicates how many times the tweet has been liked by Twitter users. It is a non-negative integer.
• retweet_count: The number of times this tweet has been retweeted. It is a non-negative integer.
• user_verified: When true, indicates that the user has a verified account, which helps the public recognize the authenticity of accounts of public interest. It is a boolean data type with two allowed values: True or False.
• user_default_profile: When true, indicates that the user has not altered the theme or background of their user profile. It is a boolean data type with two allowed values: True or False.
• user_has_extended_profile: When true, indicates that the user has an extended profile. An extended profile on Twitter allows users to provide more detailed information about themselves, such as an extended biography, a header image, details about their location, website, and other additional data. It is a boolean data type with two allowed values: True or False.
• user_followers_count: The current number of followers the account has. It is a non-negative integer.
• user_friends_count: The number of users that the account is following. It is a non-negative integer.
• user_favourites_count: The number of tweets this user has liked since the account was created. It is a non-negative integer.
• user_statuses_count: The number of tweets (including retweets) posted by the user. It is a non-negative integer.
• user_protected: When true, indicates that this user has chosen to protect their tweets, meaning their tweets are not publicly visible without their permission. It is a boolean data type with two allowed values: True or False.
• user_is_translator: When true, indicates that the user posting the tweet is a verified translator on Twitter. This means they have been recognized and validated by the platform as translators of content in different languages. It is a boolean data type with two allowed values: True or False.

Cite as

Guerrero-Contreras, G., Balderas-Díaz, S., Serrano-Fernández, A., & Muñoz, A. (2024, June). Enhancing Sentiment Analysis on Social Media: Integrating Text and Metadata for Refined Insights. In 2024 International Conference on Intelligent Environments (IE) (pp. 62-69). IEEE.

Potential Use Cases

This dataset is aimed at academic researchers and practitioners with interests in:

• Sentiment analysis and natural language processing (NLP) with a focus on AI discussions in the Spanish language.
• Social media analysis on public engagement and perception of artificial intelligence among Spanish speakers.
• Exploring correlations between user engagement metrics and sentiment in discussions about AI.

Data Format and File Type

The dataset is provided in CSV format, ensuring compatibility with a wide range of data analysis tools and programming environments.

License

The dataset is available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license, permitting sharing, copying, distribution, transmission, and adaptation of the work for any purpose, including commercial, provided proper attribution is given.

The market for AI in social media is expanding rapidly due to the increasing use of social media platforms and the rising demand for personalized content and targeted advertising. The market is expected to reach a value of $588.8 million by 2033, growing at a CAGR of 15.5% from 2025 to 2033. Key drivers include the growing adoption of AI-powered social media monitoring tools, the increasing demand for chatbots and virtual assistants, and the need for improved customer engagement and personalization. The market is segmented by type into machine learning and deep learning, and natural language processing (NLP). By application, the market is divided into retail and e-commerce, banking, financial services and insurance (BFSI), media and advertising, education, public utilities, and others. Key companies operating in the market include Google, Facebook, Microsoft, AWS, IBM, Adobe Systems, Baidu, Salesforce, Twitter, Snap, Clarabridge, Converseon, Sprinklr, Unmetric, Isentium, Cluep, Netbase, Spredfast, Synthesio, Crimson Hexagon, Hootsuite, Sprout Social, Vidora, Meltwater, Talkwalker, and others. Artificial intelligence (AI) is rapidly transforming the social media landscape. From personalized content recommendations to automated customer service, AI is helping social media companies to engage users, drive growth, and improve their bottom line.

Artificial Intelligence & Advanced Machine Learning Market size valued $137.93 Bn in 2023 & expected to reach $1790.43 Bn by 2032, at CAGR 29.2% from 2024-2032.

AI has become (again) a matter of public interest, and it is crucial to investigate how the news media intervenes in the hype and publicity around AI in different countries. At the intersection between Media Studies and Science and Technology Studies (STS), this article examines portrayals of AI and related technologies in the Chilean news media. We curated a corpus of nearly 7000 AI-related news articles from 2008 to 2023 from four Chilean newspapers. We combined an LDA topic modelling with an analysis with dictionaries of the key actors and critical issues discussed around AI. The analysis shows the explosive growth of the media coverage of AI in recent years, as well as the diversity of topics associated with AI in Chile. We found a high prominence of topics related to industry and technology, a high visibility of international actors, mostly U.S. tech companies, and a low level of mentions of critical issues around AI. Moreover, we also discuss the low coverage of the State’s AI use, the emergent use of generative AI in tech journalism, and the prominence of topics such as the arts and humanities that appear as emerging spaces for the problematisation of AI in Chile.

The report covers AI in Social Media Market Trends and it is segmented By Technology (Machine Learning and Deep Learning, NLP), Application (Sales and Marketing, Customer Experience Management, Image Recognition, Predictive Risk Assessment), Service (Managed Service, Professional Service), Organization Size (Small and Medium Enterprise, Large Enterprise) End User (Retail, E-commerce, Banking, Financial Services and Insurance (BFSI), Media and Advertising, Education, Other End-user Industries) and Geography (North America, Europe, Asia Pacific, Latin America, and Middle East and Africa). The market size and forecasts are provided regarding value (USD million) for all the above segments.

The Cognitive Media Solutions market is experiencing explosive growth, projected to reach $2.32 billion in 2025 and exhibiting a remarkable Compound Annual Growth Rate (CAGR) of 78.44%. This surge is fueled by several key factors. The increasing volume of unstructured media data, coupled with the need for efficient content analysis and management across various industries, is driving demand for sophisticated cognitive solutions. Businesses, particularly large enterprises and SMEs, are leveraging these solutions for improved customer engagement, enhanced brand reputation management, and more effective marketing campaigns. Advancements in artificial intelligence (AI), natural language processing (NLP), and machine learning (ML) are enabling more accurate and insightful media analysis, further accelerating market expansion. The integration of cognitive media solutions with existing enterprise resource planning (ERP) systems and customer relationship management (CRM) systems is streamlining operations and facilitating data-driven decision-making. The market segmentation reveals a strong presence of both large enterprises and SMEs. While large enterprises lead in adoption due to their substantial resources, SMEs are rapidly adopting these solutions to enhance efficiency and competitiveness. North America currently holds a significant market share, driven by early adoption and a well-established technological infrastructure. However, Asia-Pacific (APAC) is poised for significant growth in the coming years, fueled by increasing digitalization and technological advancements across rapidly developing economies like China and Japan. Competitive pressures are shaping the market landscape, with established players like Adobe, Microsoft, and IBM competing against innovative startups. Strategic partnerships, acquisitions, and continuous product development are key competitive strategies driving innovation and market penetration. While the market faces challenges like data privacy concerns and the need for robust data security measures, the overall outlook remains exceptionally positive, driven by the undeniable value proposition of cognitive media solutions in a data-rich world.

During an August 2023 survey among chief marketing officers (CMOs) in Canada and the United States, around 53 percent of respondents listed data analysis among their plans for prioritizing focus on artificial intelligence (AI) over the next 12 months. Strategy, creative and content development for media use ranked second with 49 percent, while audience targeting and segmentation rounded up the top three, mentioned by 45 percent.

We have conducted a quantitative visual content analysis of illustrated German national print media coverage on AI. Our analysis focuses on two time periods: on the one hand the time period between January 1 and December 31, 2019 has been analyzed and on the other hand the time period between November 1, 2022 and October 31, 2023. As news media titles, we chose six (leading) national quality newspapers and news magazines in Germany, namely: Süddeutsche Zeitung (SZ), Frankfurter Allgemeine Zeitung (FAZ), Die Welt (DW), taz, Der Spiegel, and Die Zeit. All illustrated articles during the analysis period that contained the keywords ‘artificial intelligence’ or ‘AI’[1] in their headline or subtitle (focus on articles that cover AI as a main topic) were selected for analysis. Our search resulted in 589 illustrated articles with n = 818 images in total (some articles contained more than one image). For each image we manually coded- formal features like medium, date, department and visualization type of the image,- the visual objects with different levels of detail (per image, several image objects [like human, robot, computer etc.] with multiple specifying subcategories could be coded, for example if an image shows a human and a robot at the same time),- the main AI subject covered in the article (using inductive coding of the article headlines, subtitles and text),- and the framing elements potential uses of AI (visualization of potential or real uses of AI in all areas of life with dominant positive connotations), danger potential (visualization of dangers that may arise from widespread hasty or non-critically reflected deployment of AI applications), competition (visualization of existing national and international competition in AI development, research and implementation, human role model (visualizations that show humans as an ideal role model for hard- and software, whose control is based on AI), (further) development (visualizations that focus on previous developments in the field of AI but also developmental work, which is still ongoing), and cultural and artistic debate (visualizations that show the cultural or artistic engagement with AI as a technology).[1] German search string: “Künstliche* Intelligenz” OR KI

The global market for data lens (visualizations of data) is experiencing robust growth, driven by the increasing adoption of data analytics across diverse industries. This market, estimated at $50 billion in 2025, is projected to achieve a compound annual growth rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising volume and complexity of data necessitate effective visualization tools for insightful analysis. Businesses are increasingly relying on interactive dashboards and data storytelling techniques to derive actionable intelligence from their data, fostering the demand for sophisticated data visualization solutions. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of data visualization platforms, enabling automated insights generation and predictive analytics. This creates new opportunities for vendors to offer more advanced and user-friendly tools. Finally, the growing adoption of cloud-based solutions is further accelerating market growth, offering enhanced scalability, accessibility, and cost-effectiveness. The market is segmented across various types, including points, lines, and bars, and applications, ranging from exploratory data analysis and interactive data visualization to descriptive statistics and advanced data science techniques. Major players like Tableau, Sisense, and Microsoft dominate the market, constantly innovating to meet evolving customer needs and competitive pressures. The geographical distribution of the market reveals strong growth across North America and Europe, driven by early adoption and technological advancements. However, emerging markets in Asia-Pacific and the Middle East & Africa are showing significant growth potential, fueled by increasing digitalization and investment in data analytics infrastructure. Restraints to growth include the high cost of implementation, the need for skilled professionals to effectively utilize these tools, and security concerns related to data privacy. Nonetheless, the overall market outlook remains positive, with continued expansion anticipated throughout the forecast period due to the fundamental importance of data visualization in informed decision-making across all sectors.

Please cite the following paper when using this dataset:

N. Thakur, V. Su, M. Shao, K. Patel, H. Jeong, V. Knieling, and A. Bian “A labelled dataset for sentiment analysis of videos on YouTube, TikTok, and other sources about the 2024 outbreak of measles,” Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, USA, 29 June - 4 July 2024. (Accepted as a Late Breaking Paper, Preprint Available at: https://doi.org/10.48550/arXiv.2406.07693)

Abstract

This dataset contains the data of 4011 videos about the ongoing outbreak of measles published on 264 websites on the internet between January 1, 2024, and May 31, 2024. These websites primarily include YouTube and TikTok, which account for 48.6% and 15.2% of the videos, respectively. The remainder of the websites include Instagram and Facebook as well as the websites of various global and local news organizations. For each of these videos, the URL of the video, title of the post, description of the post, and the date of publication of the video are presented as separate attributes in the dataset. After developing this dataset, sentiment analysis (using VADER), subjectivity analysis (using TextBlob), and fine-grain sentiment analysis (using DistilRoBERTa-base) of the video titles and video descriptions were performed. This included classifying each video title and video description into (i) one of the sentiment classes i.e. positive, negative, or neutral, (ii) one of the subjectivity classes i.e. highly opinionated, neutral opinionated, or least opinionated, and (iii) one of the fine-grain sentiment classes i.e. fear, surprise, joy, sadness, anger, disgust, or neutral. These results are presented as separate attributes in the dataset for the training and testing of machine learning algorithms for performing sentiment analysis or subjectivity analysis in this field as well as for other applications. The paper associated with this dataset (please see the above-mentioned citation) also presents a list of open research questions that may be investigated using this dataset.

The AI Enterprise Data Analytics Platform market is projected to reach a colossal market size of USD 5393 million by 2033, exhibiting a remarkable CAGR of 12.9% during the forecast period (2025-2033). The surging demand for data-driven decision-making, process automation, and improved operational efficiency is fueling market growth. As enterprises strive to harness the vast amounts of data at their disposal, the adoption of AI-powered analytics platforms is becoming increasingly prevalent. These platforms offer advanced capabilities such as predictive analytics, machine learning, and natural language processing, enabling organizations to extract valuable insights, identify patterns, and make informed decisions. The market is witnessing the emergence of key drivers, including the proliferation of IoT devices, the growing adoption of cloud computing, and the increasing awareness of data privacy and security. Furthermore, the rise of sectors such as fintech, healthcare, and manufacturing, where data analytics plays a crucial role in optimizing operations and improving customer experiences, is contributing to market growth. However, challenges such as the lack of skilled professionals, the high cost of implementation, and concerns over data privacy may hinder the market's expansion. Leading market players like Corraldata, Dynatrace, IBM, Microsoft, and Zoho are continuously innovating and expanding their offerings to cater to the evolving needs of enterprises, further shaping the competitive landscape of the AI Enterprise Data Analytics Platform market.

[228+ Pages Report] The global artificial intelligence (AI) market size is expected to grow from USD 137 billion in 2022 to USD 1812 billion by 2030, at a CAGR of 38% from 2023-2030

The Content Intelligence market is experiencing robust growth, projected to reach a substantial size driven by the increasing need for businesses to leverage data-driven insights for improved content strategy and performance. The market's Compound Annual Growth Rate (CAGR) of 30.81% from 2019 to 2024 indicates a significant upward trajectory. This expansion is fueled by several key factors. The rise of digital content creation and distribution necessitates sophisticated tools for analysis and optimization. Businesses are increasingly recognizing the value of understanding audience engagement, content performance, and competitor activities to refine their strategies. Moreover, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of content intelligence platforms, enabling more accurate predictions and personalized content recommendations. Segmentation within the market reveals a strong demand across various types of content (e.g., text, video, social media) and applications (e.g., marketing, customer service, brand monitoring). Leading companies are investing heavily in research and development to maintain a competitive edge, focusing on improving user experience and integrating advanced analytics features. The market's growth is not without its challenges. Data privacy concerns and the complexities associated with integrating diverse data sources represent significant hurdles. Furthermore, the cost of implementing and maintaining sophisticated content intelligence platforms can be substantial, particularly for smaller organizations. Despite these limitations, the overall market outlook remains positive. The increasing reliance on data-driven decision-making across industries, coupled with continuous technological advancements, will propel continued market expansion through 2033. The geographical distribution of the market shows strong growth across North America, Europe, and Asia-Pacific, with each region presenting unique opportunities and challenges based on its digital maturity and regulatory landscape. Future success will hinge on the ability of companies to effectively address data privacy concerns, simplify platform usability, and demonstrate a clear return on investment for their clients.