Web search volume as a predictor of academic fame: An exploration of Google trends

BACKGROUND Since the beginning of the novel coronavirus disease (COVID-19) outbreak, fake news and misleading information have circulated worldwide, which can profoundly affect public health communication. OBJECTIVE We investigated online search behavior related to the COVID-19 outbreak and the attitudes of “infodemic monikers” (ie, erroneous information that gives rise to interpretative mistakes, fake news, episodes of racism, etc) circulating in Italy. METHODS By using Google Trends to explore the internet search activity related to COVID-19 from January to March 2020, article titles from the most read newspapers and government websites were mined to investigate the attitudes of infodemic monikers circulating across various regions and cities in Italy. Search volume values and average peak comparison (APC) values were used to analyze the results. RESULTS Keywords such as “novel coronavirus,” “China coronavirus,” “COVID-19,” “2019-nCOV,” and “SARS-COV-2” were the top infodemic and scientific COVID-19 terms trending in Italy. The top five searches related to health were “face masks,” “amuchina” (disinfectant), “symptoms of the novel coronavirus,” “health bulletin,” and “vaccines for coronavirus.” The regions of Umbria and Basilicata recorded a high number of infodemic monikers (APC weighted total >140). Misinformation was widely circulated in the Campania region, and racism-related information was widespread in Umbria and Basilicata. These monikers were frequently searched (APC weighted total >100) in more than 10 major cities in Italy, including Rome. CONCLUSIONS We identified a growing regional and population-level interest in COVID-19 in Italy. The majority of searches were related to amuchina, face masks, health bulletins, and COVID-19 symptoms. Since a large number of infodemic monikers were observed across Italy, we recommend that health agencies use Google Trends to predict human behavior as well as to manage misinformation circulation in Italy.

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Prediction of Zika-confirmed cases in Brazil and Colombia using Google Trends

Epidemiology and Infection ◽

10.1017/s0950268818002078 ◽

2018 ◽

Vol 146 (13) ◽

pp. 1625-1627 ◽

Cited By ~ 11

Author(s):

S. Morsy ◽

T.N. Dang ◽

M.G. Kamel ◽

A.H. Zayan ◽

O.M. Makram ◽

...

Keyword(s):

Zika Virus ◽

Surveillance System ◽

Web Search ◽

Low Cost ◽

Google Trends ◽

Search Query ◽

Time Series Regression ◽

Search Volume ◽

Advance Time ◽

Google Search

AbstractZika virus infection in humans has been linked to severe neurological sequels and foetal malformations. The rapidly evolving epidemics and serious complications made the frequent updates of Zika virus mandatory. Web search query has emerged as a low-cost real-time surveillance system to anticipate infectious diseases’ outbreaks. Hence, we developed a prediction model that could predict Zika-confirmed cases based on Zika search volume in Google Trends. We extracted weekly confirmed Zika cases of two epidemic countries, Brazil and Colombia. We got the weekly Zika search volume in the two countries from Google Trends. We used standard time-series regression (TSR) to predict the weekly confirmed Zika cases based on the Zika search volume (Zika query). The basis TSR model – using 1-week lag of Zika query and using 1-week lag of Zika cases as a control for autocorrelation – was the best for predicting Zika cases in Brazil and Colombia because it balanced the performance of the model and the advance time in the prediction. Our results showed that we could use Google search queries to predict Zika cases 1 week earlier before the outbreak. These findings are important to help healthcare authorities evaluate the outbreak and take necessary precautions.

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COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study

JMIR Public Health and Surveillance ◽

10.2196/19374 ◽

2020 ◽

Vol 6 (2) ◽

pp. e19374 ◽

Cited By ~ 46

Author(s):

Alessandro Rovetta ◽

Akshaya Srikanth Bhagavathula

Keyword(s):

Web Search ◽

Population Level ◽

Google Trends ◽

The Novel ◽

Fake News ◽

Search Activity ◽

Campania Region ◽

Search Volume ◽

Government Websites ◽

Novel Coronavirus

Background Since the beginning of the novel coronavirus disease (COVID-19) outbreak, fake news and misleading information have circulated worldwide, which can profoundly affect public health communication. Objective We investigated online search behavior related to the COVID-19 outbreak and the attitudes of “infodemic monikers” (ie, erroneous information that gives rise to interpretative mistakes, fake news, episodes of racism, etc) circulating in Italy. Methods By using Google Trends to explore the internet search activity related to COVID-19 from January to March 2020, article titles from the most read newspapers and government websites were mined to investigate the attitudes of infodemic monikers circulating across various regions and cities in Italy. Search volume values and average peak comparison (APC) values were used to analyze the results. Results Keywords such as “novel coronavirus,” “China coronavirus,” “COVID-19,” “2019-nCOV,” and “SARS-COV-2” were the top infodemic and scientific COVID-19 terms trending in Italy. The top five searches related to health were “face masks,” “amuchina” (disinfectant), “symptoms of the novel coronavirus,” “health bulletin,” and “vaccines for coronavirus.” The regions of Umbria and Basilicata recorded a high number of infodemic monikers (APC weighted total >140). Misinformation was widely circulated in the Campania region, and racism-related information was widespread in Umbria and Basilicata. These monikers were frequently searched (APC weighted total >100) in more than 10 major cities in Italy, including Rome. Conclusions We identified a growing regional and population-level interest in COVID-19 in Italy. The majority of searches were related to amuchina, face masks, health bulletins, and COVID-19 symptoms. Since a large number of infodemic monikers were observed across Italy, we recommend that health agencies use Google Trends to predict human behavior as well as to manage misinformation circulation in Italy.

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Predicting the Number of GHB-Related Toxicologic Admissions Using Google Trends Data

International Journal of Mental Health and Addiction ◽

10.1007/s11469-021-00706-9 ◽

2021 ◽

Author(s):

Máté Kapitány-Fövény ◽

Tamás Ferenci ◽

Zsolt Demetrovics ◽

Mihály Sulyok

Keyword(s):

Web Search ◽

External Validation ◽

Google Trends ◽

Monthly Data ◽

Admission Rates ◽

Search Volume ◽

Subtle Effect ◽

Gamma Hydroxybutyrate ◽

Two Peaks ◽

Source Of Information

Abstract In the era of novel psychoactive substances (NPS), the internet became a relevant source of information and purchase for those who consume psychoactive drugs. Parallelly, a growing body of research aim to utilize web search metrics (most commonly by relying on Google Trends data) in the prediction of substance use-related trends, including epidemiological forecasting. The main goal of the current study was to assess the utility of web search queries in the prediction of Gamma-hydroxybutyrate (GHB)-related toxicologic admissions in Hungary by performing additive decomposition of time series to identify trend and seasonal components. Monthly data identified GHB-related search volume representing nationwide web interest towards this substance was found to be a significant covariate of admission rates; the seasonal component showed two peaks in the admission rates: one in December/January and another one in May, whereas more admissions on the weekends were observed as compared to weekday data in Hungary. By taking into account the subtle effect sizes of this study, these results suggest that Google Trends data may be useful in forecasting toxicologic admissions on a monthly level, yet a number of limitations should be considered when interpreting these associations. Web search metrics can therefore be used for early warning purposes in the field of toxicology as well. An external validation approach is also suggested by the authors.

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COVID-19 Related Web Search Behaviors: An Analytical Study of Google Trends-based Query Volumes in Indonesia (Preprint)

10.2196/preprints.23650 ◽

2020 ◽

Author(s):

Vita Widyasari ◽

Karisma Trinanda Putra ◽

Jiun-Yi Wang

Keyword(s):

Web Search ◽

Public Awareness ◽

Relevant Information ◽

Community Response ◽

Google Trends ◽

P Value ◽

Basic Information ◽

First Case ◽

The Government ◽

Economic Anxiety

BACKGROUND The volume of search keywords on Google can be used as a reference to an ongoing online trend during COVID-19 pandemic. OBJECTIVE This study was aimed to estimate the responsiveness and public awareness in early days of the COVID-19 outbreak in Indonesia using Google Trends relative search volumes (RSV). METHODS Sixty terms or keywords forming six topics included in the analysis were basic information, prevention, government policy, socio-economic, anxiety, and other issues related to COVID-19. All these keywords were checked for surveillance purposes between January 1 and May 4, 2020. The Python programming language was used for data mining from Google Trends databases. Correlation analysis was conducted to examine the correlations between the incidence of COVID-19 and the search terms. RESULTS Community response and awareness in the six topics were associated with the number of COVID-19 cases (r range between 0.570-0.825, P-value<.005). Before the first case announced in Indonesian, the prominent topics were basic information and other issues. One month after the first case, all topics experienced an increase in RSV. In the phase of outbreak, socio-economic and anxiety got much more attentions. CONCLUSIONS The government should consider to optimize the internet as a media for timely delivering most relevant information and dynamically respond massive queries, and improve health communications to increase public awareness and intention to prevent the disease.

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Increase in searches for erectile dysfunction during winter: seasonal variation evidence from Google Trends in the United States

International Journal of Impotence Research ◽

10.1038/s41443-020-00397-1 ◽

2021 ◽

Author(s):

Belén Mora Garijo ◽

Jonathan E. Katz ◽

Aubrey Greer ◽

Mia Gonzalgo ◽

Alejandro García López ◽

...

Keyword(s):

Prostate Cancer ◽

United States ◽

Erectile Dysfunction ◽

Seasonal Variation ◽

Kidney Stones ◽

Seasonal Pattern ◽

The United States ◽

Google Trends ◽

Internet Search ◽

Search Volume

AbstractSeveral diseases associated with erectile dysfunction (ED), such as type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), are known to have seasonal variation, with increased incidence during winter months. However, no literature exists on whether this chronological-seasonal evolution is also present within ED symptomatology. We hypothesized ED would follow the seasonal pattern of its lifestyle-influenced comorbid conditions and exhibit increased incidence during winter months. In order to investigate the seasonal variation of ED in the United States between 2009 and 2019, Internet search query data were obtained using Google Trends. Normalized search volume was determined during the winter and summer seasons for ED, other diseases known to be significantly associated with ED (T2DM and CAD), kidney stones (positive control), and prostate cancer (negative control). There were significantly more internet search queries for ED during the winter than during the summer (p = 0.001). CAD and T2DM also had significantly increased search volume during winter months compared to summer months (p < 0.001 and p = 0.011, respectively). By contrast, searches for kidney stones were significantly increased in the summer than in the winter (p < 0.001). There was no significant seasonal variation in the relative search frequency for prostate cancer (p = 0.75). In conclusion, Google Trends internet search data across a ten-year period in the United States suggested a seasonal variation in ED, which implies an increase in ED during winter. This novel finding in ED epidemiology may help increase awareness of ED’s associated lifestyle risk factors, which may facilitate early medical evaluation and treatment for those at risk of both ED and cardiovascular disease.

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Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines

10.1101/424630 ◽

2018 ◽

Author(s):

Howell T. Ho ◽

Thaddeus M. Carvajal ◽

John Robert Bautista ◽

Jayson Dale R. Capistrano ◽

Katherine M. Viacrusis ◽

...

Keyword(s):

Thematic Analysis ◽

Cross Correlation ◽

Temporal Relationship ◽

The Philippines ◽

Google Trends ◽

Health Concern ◽

Epidemiological Methods ◽

Search Queries ◽

Search Volume ◽

Dengue Outbreaks

AbstractDengue is a major public health concern and an economic burden in the Philippines. Despite the country’s improved dengue surveillance, it still suffers from various setbacks and therefore needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study aims to assess the temporal relationship of GDT and dengue incidence in Metropolitan Manila from previous years and examine web search behavior of the population towards the disease. The study collated and organized the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the spatial and temporal dengue incidence. The relative search volume of the term ‘dengue’ and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google trends platform. Data processing of GDT and dengue incidence was performed by conducting an ‘adjustment’ procedure and subsequently used for correlation and cross-correlation analyses. Moreover, a thematic analysis was employed on the top dengue-related search queries. Results revealed a high temporal relationship between GDT and dengue incidence when either one of the variables is adjusted. Cross-correlation showed that there is delayed effect (1-2 weeks) of GDT to dengue incidence, demonstrating its potential in predicting future dengue outbreaks and patterns in Metropolitan Manila. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito and (e) other diseases where the majority of the search queries was ‘signs and symptoms’ which indicate the health-seeking behavior of the population towards the disease.

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Seasonal variations and public search interests in Toxoplasma: a 16-year retrospective analysis of big data on Google Trends

Transactions of the Royal Society of Tropical Medicine and Hygiene ◽

10.1093/trstmh/traa147 ◽

2020 ◽

Author(s):

Lei Liu ◽

Peng Wang ◽

Su-Qin Jiang ◽

Zi-Rong Zhong ◽

Ting-Zheng Zhan ◽

...

Keyword(s):

New Zealand ◽

Google Trends ◽

Seasonal Patterns ◽

Search Term ◽

Internet Search ◽

Search Volume ◽

The Usa ◽

Search Data ◽

Relative Search Volume ◽

The Uk

Abstract Background This study aims to understand whether there is a seasonal change in the internet search interest for Toxoplasma by using the data derived from Google Trends (GT). Methods The present study searched for the relative search volume (RSV) for the search term ‘Toxoplasma’ in GT within six major English-speaking countries (Australia, New Zealand [Southern Hemisphere] and Canada, Ireland, the UK and the USA [Northern Hemisphere] from 1 January 2004 to 31 December 2019, utilizing the category of ‘health’. Data regarding the RSV of Toxoplasma was obtained and further statistical analysis was performed in R software using the ‘season’ package. Results There were significantly seasonal patterns for the RSV of the search term ‘Toxoplasma’ in five countries (all p<0.05), except for the UK. A peak in December–March and a trough in July–September (Canada, Ireland, the UK and the USA) were observed, while a peak in June/August and a trough in December/February (Australia, New Zealand) were also found. Moreover, the presence of seasonal patterns regarding RSV for ‘Toxoplasma’ between the Southern and Northern Hemispheres was also found (both p<0.05), with a reversed meteorological month. Conclusions Overall, our study revealed the seasonal variation for Toxoplasma in using internet search data from GT, providing additional evidence on seasonal patterns in Toxoplasma.

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Predicting Public Interest in Nonsurgical Cosmetic Procedures Using Google Trends

Aesthetic Surgery Journal ◽

10.1093/asj/sjz264 ◽

2019 ◽

Vol 40 (11) ◽

pp. 1253-1262 ◽

Cited By ~ 2

Author(s):

Jonathan D Tijerina ◽

Shane D Morrison ◽

Ian T Nolan ◽

Matthew J Parham ◽

Rahim Nazerali

Keyword(s):

Hyaluronic Acid ◽

Public Interest ◽

The United States ◽

Google Trends ◽

Search Term ◽

Data Set ◽

Fat Transfer ◽

Laser Hair Removal ◽

Search Terms ◽

Search Volume

Abstract Background Google Trends (GT) provides cost-free, customizable analyses of search traffic for specified terms entered into Google’s search engine. GT may inform plastic surgery marketing decisions and resource allocation. Objectives The aim of this study was to determine GT’s utility in tracking and predicting public interest in nonsurgical cosmetic procedures and to examine trends over time of public interest in nonsurgical procedures. Methods GT search volume for terms in 6 ASPS and ASAPS nonsurgical procedure categories (Botox injections, chemical peel, laser hair removal, laser skin resurfacing, microdermabrasion and soft tissue fillers [subcategories: collagen, fat, and hyaluronic acid]) were compared with ASPS and ASAPS case volumes for available dates between January 2004 and March 2019 with the use of univariate linear regression, taking P < 0.01 as the cutoff for significance. Results Total search volume varied by search term within the United States and internationally. Significant positive correlations were demonstrated for 17 GT terms in all 6 ASPS and ASAPS categories: “Botox®,” “collagen injections,” “collagen lip injections” with both databases; and “chemical skin peel,” “skin peel,” “acne scar treatment,” “CO2 laser treatment,” “dermabrasion,” “collagen injections,” “collagen lip injections,” “fat transfer,” “hyaluronic acid fillers,” “hyaluronic acid injection,” “hyaluronic acid injections,” “Juvederm®,” and “fat transfer” with just 1 database. Many search terms were not significant, emphasizing the need for careful selection of search terms. Conclusions Our analysis further elaborates on recent characterization of GT as a powerful and intuitive data set for plastic surgeons, with the potential to accurately gauge global and national interest in topics and procedures related to nonsurgical cosmetic procedures.

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Discovering business information from search engine query data

Online Information Review ◽

10.1108/oir-08-2013-0190 ◽

2014 ◽

Vol 38 (4) ◽

pp. 562-574 ◽

Cited By ~ 8

Author(s):

Liwen Vaughan

Keyword(s):

Search Engine ◽

Business Performance ◽

Google Trends ◽

Volume Data ◽

Content Type ◽

Search Volume ◽

Business Information ◽

Position Data ◽

Search Data ◽

One Year

Purpose – The purpose of this paper is to examine the feasibility of discovering business information from search engine query data. Specifically the study tried to determine whether search volumes of company names are correlated with the companies’ business performance and position data. Design/methodology/approach – The top 50 US companies in the 2012 Fortune 500 list were included in the study. The following business performance and position data were collected: revenues, profits, assets, stockholders’ equity, profits as a percentage of revenues, and profits as a percentage of assets. Data on the search volumes of the company names were collected from Google Trends, which is based on search queries users enter into Google. Google Trends data were collected in the two scenarios of worldwide searches and US searches. Findings – The study found significant correlations between search volume data and business performance and position data, suggesting that search engine query data can be used to discover business information. Google Trends’ worldwide search data were better than the US domestic search data for this purpose. Research limitations/implications – The study is limited to only one country and to one year of data. Practical implications – Publicly available search engine query data such as those from Google Trends can be used to estimate business performance and position data which are not always publicly available. Search engine query data are timelier than business data. Originality/value – This is the first study to establish a relationship between search engine query data and business performance and position data.

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