The Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data in 210 distinct locations in the United States. This Google dataset is hosted in Google BigQuery as part of Google Cloud's Datasets solution and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

The International Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data for each country and region across the globe, where data is available. This Google dataset is hosted in Google BigQuery as part of Google Cloud's Datasets solution and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

documents for the paper "Predicting Chinese consumption using data from Baidu and Google"

This is the figure and dataset inventory for the article: The detection of emerging trends using Wikipedia traffic data and context networks

Saudi Arabia Google Search Trends: Online Shopping: eBay data was reported at 29.000 Score in 14 May 2025. This records a decrease from the previous number of 31.000 Score for 13 May 2025. Saudi Arabia Google Search Trends: Online Shopping: eBay data is updated daily, averaging 26.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 65.000 Score in 11 Sep 2022 and a record low of 0.000 Score in 10 Jun 2023. Saudi Arabia Google Search Trends: Online Shopping: eBay data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Saudi Arabia – Table SA.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.

Statistics results of Baidu index and Google trends on keywords related to the epidemic from January 10 to February 28

Context

The data was extracted to be used for my submission to the 2020 kaggle online survey. You can find the related submission here. I used it to analyze the searches related to Automated Machine learning.

Content

The data consists of google trends for AutoML /Automated machine learning. This data is Aggregated, **Anonymised **, Indexed and Normalized. The dataset consists of four files:

• Timeline Data(2015-2020) Timeline data shows interest over time. The Numbers represent search interest relative to the highest point on the chart for the given region and time. A value of 100 is the peak popularity for the term. A value of 50 means that the term is half as popular. A score of 0 means that there was not enough data for this term. I have used the search data from the year 2015 to 2020.

• GeoMap data for the year 2020 GeoMap data shows Interest by sub-region. It essentially highlights locations where the search term was most popular during the specified time frame. Values are calculated on a scale from 0 to 100, where 100 is the location with the most popularity as a fraction of total searches in that location, a value of 50 indicates a location that is half as popular. A value of 0 indicates a location where there was not enough data for this term.

• Related Entities data for the year 2020 Related entities mean users searching for your term also searched for these topics. Scoring is on a relative scale where a value of 100 is the most commonly searched topic and a value of 50 is a topic searched half as often as the most popular term, and so on

• Related Queries data Related Queries mean users searching for your term also searched for these queries. Scoring is on a relative scale where a value of 100 is the most commonly searched query, 50 is a query searched half as often as the most popular query, and so on.

The explanations have been taken from the Google trend official site.

Acknowledgements

• Banner Image: People vector created by pch.vector - www.freepik.com
• Google Trends

Useful links: - Google Trends - Google News Lab - @GoogleTrends

"Iceland" and "Google" were the most googled terms in Iceland in 2024. The terms had a search engine index of *** and ** respectively. The third most common term was "Translate," with an index of **. Among other popular search terms were "Reykjavik", "You" and "Google Translate".

Primary headache disorders, such as tension-type headaches (TTH) and migraines, are prevalent and often triggered by environmental factors like weather changes. This study used Google Trends data (2019–2023) and the Ap index to investigate the role of geomagnetic activity in triggering headaches. A total of 261 observations revealed a statistically significant but weak negative correlation between low geomagnetic activity and increased search interest for "migraine" and "headache." TTH showed greater sensitivity to low geomagnetic activity than migraines, suggesting different mechanisms. These findings highlight the need for further research into geomagnetic influences on headache disorders.

1. The publication of “More than 75 percent decline over 27 years in total flying insect biomass in protected areas” by Hallmann et al. in October 2017 gained vast media coverage in Germany. The insect crisis as conservation topic has received little attention among the public before, but since media influences people’s awareness, we investigated i) whether the study publication induced increased awareness among the German public for insect die-off, and ii) whether it contributed to people’s intentions to undertake insect protecting actions.
2. We used Google Trends to examine the people’s internet activity in terms of keywords relevant to our research question.
3. A high peak in Google searches for insect die-off (Insektensterben) was indeed visible just after the study publication, and search volume remained significantly higher for the following six months, confirming that the topic gained attention.
4. Searches for the three keywords insect hotel, bee friendly and bee meadow increased significantly over the summers of the years 2017 to 2019. This suggests that intentions to undertake these simple insect protecting actions rose as well. The results propose that media should use the window of opportunity opened by shocking news about a crisis to spread information on feasible counteractions.
5. Due to the prevailing topicality in the media and the already increased awareness and willingness to action among the population, conservation organizations can take advantage of the situation by communicating practical conservation measures to the general public in cooperation with media agencies or via own channels such as press releases and social media campaigns.

Methods The data was downloaded from Google Trends. It was searched for the index of search activity for the four German keywords "Insektensterben" ("insect die-off"), "Insektenhotel" ("insect hotel"), "bienenfreundlich" ("bee friendly") and "Bienenweide" ("bee meadow"). For all four keywords, query data was used rather than query collections, which is an additional feature of Google trends that includes related searches. The geographical range was restricted to Germany, and data was downloaded for the time span between January 3, 2016, and December 22, 2019. It was then analyzed with R, where the data sets were divided into different sections and compared with each other.

Parameter estimates based on a negative binomial regression using median price and a two-week moving average of the Google Trends swine flu index (first part).

Dataset of raw weekly GT data and weekly new cases of Ebola as according to the WHO patient database and situation report at the global level (Sheet 1); in the three main affected West African Ebola countries (Guinea – Sheet 2, Sierra Leone – Sheet 3 and Liberia – Sheet 4); raw weekly GT data in all countries where primary cases of Ebola were registered and Pearson’s correlations (Sheet 5); total GT RSV and the total number of Ebola cases per country (Sheet 6). (XLSX 44 kb)

In January 2025, Google accounted for 93.89 percent of the global mobile search engine market worldwide. Ever since the release of Google Search in 1997, the company's search engine has dominated the search engine market, maintaining a margin of more than 93 percentage points since January 2015. Currently owned by the parent corporation Alphabet Inc., Google has one of the highest tech company revenues, with roughly 305.63 billion U.S. dollars in 2023.

Results of seasonal Mann-Kendall trend test on the search volume in Google for different topics using different benchmark keywords.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

"Clima" weather was the most probed query in the Google search engine in Brazil in 2024, indexing at 100 in terms of search volume. Compared to the top ranking search result, the weather forecast-related terms "Tempo" and "Previsão do tempo" were also some of the most searched terms on the engine, scoring index values of 77 and 28. Additionally, the messenger solution "WhatsApp" and "WhatsApp Web" scored relative index values of 78 and 59 each.

Google Mobility Changes: Parks: Indonesia data was reported at 35.000 % in 30 Sep 2022. This records a decrease from the previous number of 42.000 % for 29 Sep 2022. Google Mobility Changes: Parks: Indonesia data is updated daily, averaging -6.000 % from Feb 2020 (Median) to 30 Sep 2022, with 959 observations. The data reached an all-time high of 214.000 % in 04 May 2022 and a record low of -58.000 % in 26 Apr 2020. Google Mobility Changes: Parks: Indonesia data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Indonesia – Table ID.Google.GM: Mobility Trends: Parks.

Between January 1st and December 31st, 2024, "Wetter" (Weather) was the most popular search query on the Google search engine in Germany. "Google" was ranked second, reaching an index point value of only 50 relative to the top search query ("Wetter").

Indonesia Google Search Trends: Online Movie: Pornhub data was reported at 15.000 Score in 15 May 2025. This stayed constant from the previous number of 15.000 Score for 14 May 2025. Indonesia Google Search Trends: Online Movie: Pornhub data is updated daily, averaging 15.000 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 56.000 Score in 03 May 2022 and a record low of 0.000 Score in 14 Feb 2023. Indonesia Google Search Trends: Online Movie: Pornhub data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Indonesia – Table ID.Google.GT: Google Search Trends: by Categories.