Context

Time-based Popularity:

Tracks search interest over time, showing peaks and troughs in popularity for specific keywords.

Regional Insights:

Provides data on search trends by location, allowing for geographic comparisons of interest.

Related Queries:

Lists associated search terms, highlighting related topics that are frequently searched alongside the primary keywords.

Top vs. Rising Trends:

Distinguishes between the most popular queries and those with a sharp increase in search volume.

Category Analysis:

Organizes search data by category, enabling focused insights into specific industries, interests, or demographic groups.

Search Volume Index: Uses an index score (0–100) to represent search volume relative to the highest point on the chart for the selected region and time.

Real-time Data Availability:

Offers access to both historical and real-time data, ideal for identifying ongoing or emerging trends.

In the week from October 19 to 25, 2025, global Google searches for the word "ChatGPT" reached a peak of 100 index points, indicating a significant increase in interest and thus the highest interest over the observed period. On October 21, 2025, OpenAI introduced ChatGPT Atlas, a web browser with ChatGPT built in. Interest in the chatbot, developed by U.S.-based OpenAI and launched in November 2022, started rising in the week ending December 3, 2022. ChatGPT, which stands for Chat Generative Pre-trained Transformer, is an AI-powered auto-generative text system able to give human-sounding replies and reproduce human-like interactions when prompted.

It starts with a simple habit: you open your browser and type a question. A few keystrokes later, Google gives you answers, videos, maps, and suggestions before you even finish your thought. For billions of people around the world, this daily interaction is second nature. But behind that blinking cursor...

From September 2024 to September 2025, global interest in the search term “***********” on Google increased overall. Over the period considered, the keyword reached its highest level of popularity in the week ending **************. Meanwhile, Google searches for the term “**************” peaked in the week ending ***************.

explain the relationship between DMA, FIPS and county

ChatGPT said: Here's a breakdown of the relationship between DMA, FIPS, and county:

🗺️ 1. County A county is a geographic and administrative subdivision of a U.S. state.

For example: Cook County in Illinois or Los Angeles County in California.

The U.S. has over 3,000 counties or county-equivalents.

🔢 2. FIPS Code FIPS = Federal Information Processing Standards code.

Used to uniquely identify geographic areas like states and counties.

It consists of:

State FIPS (2 digits) — e.g., California = 06

County FIPS (3 digits) — e.g., Los Angeles County = 037

Together: 06037 (California + Los Angeles County)

FIPS codes are used in datasets, GIS, and federal data standards to track data consistently across agencies.

📺 3. DMA (Designated Market Area) DMA is a geographic region defined by Nielsen where the population receives the same (or similar) TV and radio content.

Used in advertising, media, and Google Trends to segment the market by media consumption patterns.

There are 210 DMAs in the U.S., each labeled by Nielsen with a DMA code or name (e.g., "New York", "Chicago", "Palm Springs").

📌 How They Relate Concept Level Code Type Example County Local FIPS Los Angeles County (06037) FIPS Code System Numeric Encodes state + county DMA Media Region Name/Index Los Angeles DMA

One DMA contains multiple counties.

Example: The Los Angeles DMA includes Los Angeles County, Orange County, Ventura County, etc.

Each county has a unique FIPS code, but a DMA might span counties in multiple states.

When mapping or analyzing data (e.g., in GIS or Google Trends), you often merge county-level data (FIPS) into DMAs for media or market analysis.

🧭 Example State County FIPS DMA Name DMA Code California Los Angeles 06037 Los Angeles 803 California Orange 06059 Los Angeles 803 California Riverside 06065 Palm Springs 804

👉 DMA for FIPS 02013?

Alaska is unique: it’s sparsely populated and has limited Nielsen DMA coverage.

Most of rural Alaska does not belong to a defined DMA. Instead, large parts of Alaska are treated as “non-DMA” or are grouped into a single large DMA (often labeled Anchorage DMA if included).

Recent research suggests that search volumes of the most popular search engine worldwide, Google, provided via Google Trends, could be associated with national suicide rates in the USA, UK, and some Asian countries. However, search volumes have mostly been studied in an ad hoc fashion, without controls for spurious associations. This study evaluated the validity and utility of Google Trends search volumes for behavioral forecasting of suicide rates in the USA, Germany, Austria, and Switzerland. Suicide-related search terms were systematically collected and respective Google Trends search volumes evaluated for availability. Time spans covered 2004 to 2010 (USA, Switzerland) and 2004 to 2012 (Germany, Austria). Temporal associations of search volumes and suicide rates were investigated with time-series analyses that rigorously controlled for spurious associations. The number and reliability of analyzable search volume data increased with country size. Search volumes showed various temporal associations with suicide rates. However, associations differed both across and within countries and mostly followed no discernable patterns. The total number of significant associations roughly matched the number of expected Type I errors. These results suggest that the validity of Google Trends search volumes for behavioral forecasting of national suicide rates is low. The utility and validity of search volumes for the forecasting of suicide rates depend on two key assumptions (“the population that conducts searches consists mostly of individuals with suicidal ideation”, “suicide-related search behavior is strongly linked with suicidal behavior”). We discuss strands of evidence that these two assumptions are likely not met. Implications for future research with Google Trends in the context of suicide research are also discussed.

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.

Kyrgyzstan Google Search Trends: Jobs Searching: Indeed data was reported at 0.000 Score in 29 Nov 2025. This stayed constant from the previous number of 0.000 Score for 28 Nov 2025. Kyrgyzstan Google Search Trends: Jobs Searching: Indeed data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 29 Nov 2025, with 1460 observations. The data reached an all-time high of 86.000 Score in 16 Nov 2024 and a record low of 0.000 Score in 29 Nov 2025. Kyrgyzstan Google Search Trends: Jobs Searching: Indeed data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Kyrgyzstan – Table KG.Google.GT: Google Search Trends: by Categories.

Dataset. The dataset is provided in a comma separated value file (csv).

Introduction

Google Search Statistics: Google Search stands as the dominant global search engine, playing a crucial role in helping users find information, make informed decisions, and engage with online content. As digital habits evolve, Google remains at the forefront, influencing how people access websites, engage with brands, and discover new services.

Through advancements in AI, personalized results, and the growing trend of mobile searches, Google Search continuously refines its approach to deliver more relevant and efficient user experiences. Consequently, staying updated on Google Search trends and statistics is crucial for businesses, marketers, and analysts seeking to refine their strategies and increase visibility in a rapidly evolving digital landscape.

As of May 2025, global Google searches for the word "Grindr" have generated a slight global increase over the previous five months. During the analyzed period, interest in the LGBTQ-focused dating app peaked on the week of July 14, 2024, with 100 index points.

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.

Morocco Google Search Trends: Government Measures: Government Subsidy data was reported at 0.000 Score in 29 Nov 2025. This stayed constant from the previous number of 0.000 Score for 28 Nov 2025. Morocco Google Search Trends: Government Measures: Government Subsidy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 29 Nov 2025, with 1460 observations. The data reached an all-time high of 9.000 Score in 24 Aug 2023 and a record low of 0.000 Score in 29 Nov 2025. Morocco Google Search Trends: Government Measures: Government Subsidy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Morocco – Table MA.Google.GT: Google Search Trends: by Categories.

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

Uzbekistan Google Search Trends: Travel & Accommodations: Airbnb data was reported at 2.000 Score in 30 Nov 2025. This stayed constant from the previous number of 2.000 Score for 29 Nov 2025. Uzbekistan Google Search Trends: Travel & Accommodations: Airbnb data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 30 Nov 2025, with 1461 observations. The data reached an all-time high of 24.000 Score in 29 Aug 2024 and a record low of 0.000 Score in 18 Nov 2025. Uzbekistan Google Search Trends: Travel & Accommodations: Airbnb data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Uzbekistan – Table UZ.Google.GT: Google Search Trends: by Categories.

Afghanistan Google Search Trends: Computer & Electronics: Apple data was reported at 42.000 Score in 14 May 2025. This stayed constant from the previous number of 42.000 Score for 13 May 2025. Afghanistan Google Search Trends: Computer & Electronics: Apple data is updated daily, averaging 36.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 100.000 Score in 25 Aug 2024 and a record low of 0.000 Score in 02 May 2025. Afghanistan 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 Afghanistan – Table AF.Google.GT: Google Search Trends: by Categories.

Summary of crawled data

The z-score for data from the previous 20 days was used as the values A–J, which indicate the value of the sum of forum opinion on a given date. V–Z denote formal data values (number of topics, sum of replies, sum of views, Google Trends value, and Wikipedia page views) on a given date.

BackgroundGoogle Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research.Methods and FindingsPRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ≥0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source.ConclusionGoogle Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool.

Google searches interested in the AI-powered text-to-image "Midjourney" spiked in the first 3 weeks of June 2025. On June 15, the keyword hit a popularity score of 100 index points, before starting to decrease to 75 index points to its latest measured week. Midjourney was first launched 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 April 2025, Midjourney was the most popular server on the platform, with approximately 20 million Discord user members.