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Worldwide Internet Search Popularity Monthly Data
Data Science and Analytics
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About
This time-series data tracks the worldwide popularity and market share dynamics of major internet search engines since 2009. The data provides a detailed view of the competitive landscape, showing the dominance of certain major Western search providers like Google, while also detailing the fluctuating shares of regional and specialty engines such as Baidu, YANDEX, and DuckDuckGo over the last sixteen years. This resource is essential for analysing digital market trends and the evolution of web navigation technology.
Columns
The dataset is structured across 28 columns. The first column details the Date (format YYYY-MM) of the measurement period. The remaining 27 columns provide the Share in % for various search engines, including, but not limited to: Google, bing, Yahoo!, Baidu, YANDEX, DuckDuckGo, Naver, AOL, Haosou, Sogou, Shenma, Seznam, Conduit, MSN, Mail.ru, Ecosia, Webcrawler, Daum, CocCoc, and Windows Live. The market shares are expressed as percentages, rounded to two decimal places.
Distribution
The information is saved in a CSV file format. It contains 191 records, providing monthly data spanning nearly sixteen years. The dataset size is 21.93 kB.
Usage
This data is ideal for analytical applications, including:
- Performing detailed time series analysis and forecasting related to global search engine market distribution.
- Studying competitive dynamics within the internet technology sector.
- Creating visualisations that illustrate the long-term trends and shifts in platform dominance.
- Academic or commercial research focused on digital monopolies and consumer search behaviour across different geographies.
Coverage
The data reflects global market share measurements. The temporal scope ranges from January 2009 through to October 2024, representing approximately 16 years of monthly observations.
License
CC BY-SA 3.0
Who Can Use It
- Market Analysts: To benchmark search engine performance and identify emerging platforms.
- Academics: Conducting research on technology competition and internet economy.
- Data Engineers: Utilising historical data for training predictive models.
- Business Strategists: Assessing risks and opportunities related to visibility on different search platforms.
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Attributes
Original Data Source: Worldwide Internet Search Popularity Monthly Data
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