No description was included in this Dataset collected from the OSF

As of June 2024, global Google searches for the word "ChatGPT" increased again after a slight decline by the end of 2024. Interest in the chatbot, developed by the U.S.-based OpenAI and launched in November 2022, started rising in the week ending December 3, 2022. Recently, growing demand for information on ChatGPT made the keyword hit a peak of 100 index points during the week ending on June 2, 2024. ChatGPT, which stands for Chat Generative Pre-trained Transformer, is a chatbot and AI-powered auto-generative text system able to give human-sounding replies and reproduce human-like interactions when prompted.

Google Search Trends: Online Classroom: Zoom data was reported at 1.000 Score in 24 Nov 2024. This stayed constant from the previous number of 1.000 Score for 23 Nov 2024. Google Search Trends: Online Classroom: Zoom data is updated daily, averaging 1.000 Score from Dec 2021 (Median) to 24 Nov 2024, with 1090 observations. The data reached an all-time high of 9.000 Score in 20 Sep 2023 and a record low of 0.000 Score in 12 Feb 2024. Google Search Trends: Online Classroom: Zoom data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Nigeria – Table NG.Google.GT: Google Search Trends: by Categories.

From March 2024 to March 2025, global interest in the search term “solo travel” on Google increased overall. Over the period considered, the keyword reached its highest level of popularity in the week ending December 29, 2024. Meanwhile, Google searches for the term “digital nomads” peaked in the week ending September 8, 2024.

Iran Google Search Trends: Online Shopping: Costco data was reported at 0.000 Score in 12 Nov 2022. This stayed constant from the previous number of 0.000 Score for 11 Nov 2022. Iran Google Search Trends: Online Shopping: Costco data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 12 Nov 2022, with 347 observations. The data reached an all-time high of 26.000 Score in 26 Dec 2021 and a record low of 0.000 Score in 12 Nov 2022. Iran Google Search Trends: Online Shopping: Costco data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Iran – Table IR.Google.GT: Google Search Trends: by Categories.

Analysis of ‘TPS - Jan22 | Google Trends Kaggle search DataSet’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ankitkalauni/tps-jan22-google-trends-kaggle-search-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

"Kaggle" keyword web search (WorldWide) dataset from the google trends. I am not sure if this is going to help. I searched for Finland, Sweden, and Norway but the data is not enough.

--- Original source retains full ownership of the source dataset ---

In 2023, ectoin skincare was one of the leading skincare trends worldwide, based on a percentage growth increase in Google searches of over 160 percent. Skin streaming also registered an increase in Google searches of about 138 percent.

Google Search Trends: Online Training: Udemy data was reported at 7.000 Score in 20 Mar 2025. This records an increase from the previous number of 0.000 Score for 19 Mar 2025. Google Search Trends: Online Training: Udemy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 20 Mar 2025, with 1206 observations. The data reached an all-time high of 100.000 Score in 10 Aug 2024 and a record low of 0.000 Score in 19 Mar 2025. Google Search Trends: Online Training: Udemy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Laos – Table LA.Google.GT: Google Search Trends: by Categories.

Data collection of search data retrieved from Google Trends for brands of car manufacturers and their car brands as well as data for the brands of listed companies active in Europe. Data were retrieved using R code for a list of keywords of interest.

The aim of this project was to investigate whether data from Google Trends could be used to value brands. Currently brand valuation methods are highly complex and results are generally not available for many brands and are not comparable across brands. We downloaded Google Trends data for brands in the automotive sector and for the brands of listed companies. The data were then joined to other data about the firms and brands we collected from public sources. Analysis of this data showed that Google Trends data provides a good measure of changes to brand value for well established brands with national or global reach in the automotive sector. The data capture changes in brand value that are the result of exogeous shocks, e.g. as a result of product recalls. Google Trends data also contain information about variation in stock market value of listed companies that is not contained in data released through firms' quarterly and annual reports or in other publicly available data on intellectual property rights and citations of these rights.

The Google Trends data was complemented by data on car registrations and characteristics from various sources and data on various shocks affecting the car industry. These are not included in this dataset.

Brands are names, phrases, symbols or designs that identify particular products, which are often protected by trade marks. Trade marks help owners protect their reputation by forbidding use of their brand name by others.

Trade marks are usually registered, but not all registered marks are used. Much litigation arises over the extent of use and reputation of marks, which often results in costly surveys being run with data from trade mark registers and data from Google's search products. Data from Google's search products can be used to measure value and use of marks. In using these data, two important challenges must be overcome: heterogeneity of the data and attempts to manipulate the measures obtained. Both challenges will be addressed in the project.

The aim of this project was to improve the measurement of brand value and the measurement of trade mark use by combining data obtained from trade mark registers and data from Google's search products (Google Search, Google Trends and Google Insights for Search).

Data on search are heterogeneous because the reasons for searches are heterogeneous, they may reflect positive or negative brand interest. Additionally, attempts to manipulate Google's rankings of websites though the PageRank link analysis algorithm are legion. To overcome both problems we will consider ways of limiting search terms to obtain consistent measures of value from Google's search products.

Azerbaijan Google Search Trends: Economic Measures: Unemployment data was reported at 25.000 Score in 27 Feb 2025. This records an increase from the previous number of 15.000 Score for 26 Feb 2025. Azerbaijan Google Search Trends: Economic Measures: Unemployment data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 27 Feb 2025, with 1185 observations. The data reached an all-time high of 100.000 Score in 20 Feb 2023 and a record low of 0.000 Score in 15 Feb 2025. Azerbaijan Google Search Trends: Economic Measures: Unemployment data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Azerbaijan – Table AZ.Google.GT: Google Search Trends: by Categories.

The global interest in the term "Ukraine war" on Google Trends peaked during the week from February 27 to March 5, 2022, the first full week after Russia invaded Ukraine on February 24, 2022. Two years after the invasion began, the interest score stood at seven.

As response rates continue to decline, the need to learn more about the survey participation process remains an important task for survey researchers. Search engine data may be one possible source for learning about what information some potential respondents are looking up about a survey when they are making a participation decision. In the present study, we explored the potential of search engine data for learning about survey participation and how it can inform survey design decisions. We drew on freely available Google Trends (GT) data to learn about the use of Google Search with respect to our case study: participation in the Family Research and Demographic Analysis (FReDA) panel survey. Our results showed that some potential respondents were using Google Search to gather information on the FReDA survey. We also showed that the additional data obtained via GT can help survey researchers to discover topics of interest to respondents and geographically stratified search patterns. Moreover, we introduced different approaches for obtaining data via GT, discussed the challenges that come with these data, and closed with practical recommendations on how survey researchers might utilize GT data to learn about survey participation.

As of February 2023, Google searches interested in the AI-powered text-to-image "Midjourney" spiked twice in the previous12 months. On August 7, 2022 - shortly after the platform's public launch in July - the keyword "Midjourney" hit a popularity score of 77 index points, before starting to decrease. Google searches of Midjourney started rising again in December 2022, and peaked at 100 index points on February 5, 2023. Midjourney launched first on Discord with a dedicated server where users can produce and share the images created with the help of the integrated Discord bot. As of January 2023, Midjourney was the most popular server on the platform, with approximately 9.5 million Discord users.

This is a submission for Challenge #24 by Desights User

Click here for Challenge Details Note: This submission is in REVIEW state and is only accessible by Challenge Reviewers. So you might get errors when you try to download this asset directly from Ocean Market.

Submission Description

This report explores the relationship between Google Trends data and cryptocurrency price trends, focusing on Bitcoin. We found a significant correlation between search interest and Bitcoin's price, suggesting that heightened public interest often precedes price movements. A machine learning approach using Random Forest yielded the most accurate predictions for Bitcoin's search interest, indicating that this algorithm can effectively forecast short-term trends. The ideal lag time for predicting Bitcoin's search interest was zero, reinforcing the notion that current public interest influences market behavior. Additionally, Ethereum's weekly volume data provided insights into broader market trends, showing fluctuations that could reflect general cryptocurrency market activity. These findings offer valuable insights for traders and investors and highlight the potential for machine learning models to enhance market analysis. All code and datasets used in this study are available on GitHub, providing a resource for further exploration and validation of the results.

The code and datasets used in this report are publicly available on GitHub, providing transparency and allowing others to replicate or build upon this work. The repository can be found at https://github.com/mawutory/crypto-trends. This repository contains all the script s and data used in the analyses, allowing researchers, developers, and enthusiasts to explore and extend the findings.

Within the repository, two primary subfolders organize the resources: trends and prices. The trends folder contains datasets related to Google Trends data, including the search interest for Bitcoin and other cryptocurrencies. The prices folder holds price trend data for various cryptocurrencies, including Bitcoin, Ethereum, and others, with detailed information on price movements, volumes, and other related metrics.

To explore the code, you can navigate to the respective subfolders to find Python scripts used to preprocess data, train machine learning models, and predict trends. The datasets are also available for download, providing a basis for additional analyses or custom implementations.

Google Search Trends: Computer & Electronics: Apple data was reported at 22.000 Score in 20 Mar 2025. This records a decrease from the previous number of 23.000 Score for 19 Mar 2025. Google Search Trends: Computer & Electronics: Apple data is updated daily, averaging 21.000 Score from Dec 2021 (Median) to 20 Mar 2025, with 1206 observations. The data reached an all-time high of 89.000 Score in 14 Jan 2023 and a record low of 0.000 Score in 22 Jun 2023. Google Search Trends: Computer & Electronics: Apple data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Costa Rica – Table CR.Google.GT: Google Search Trends: by Categories.

As of June 2024, global searches for the keyword "generative AI" had experienced an increase in the previous year. The search terms for generative artificial intelligence surged in popularity from mid-February to early March 2024, hitting a score of 100 index points in the week ending March 3. Interest in "generative AI" frequently coincides with searches for ChatGPT, an AI chatbot model developed by the United States-based research company OpenAI.

"Iceland" and "Google" were the most googled terms in Iceland in 2023. The terms had a search engine index of 100 and 72 respectively. The third most common term was "translate," with an index of 68. Among other popular search terms were "Reykjavik", "MBL" and "Visir".

Google Trends search query data

Difference-in-differences estimates for lockdown-, family planning-, and fertility related search terms.

As of May 2024, global Google searches for the word "Grindr" have spiked globally over the previous three months. During the analyzed period, interest in the LGBTQ-focused dating app peaked on the week of December 25, 2023, with 100 index points.