Senses of “Selfie” Around the World From Web Search Patterns Over Extended Time

2018 ◽  
pp. 249-295
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Web Search ◽  
Search Term ◽  
Extended Time ◽  
Social Phenomena ◽  
Search Terms ◽  
Time Patterns ◽  
Search Patterns ◽  
The World ◽  
Technological Affordances ◽  
Google Search

When social phenomena and practices go viral, like “selfies,” they instantiate in different locations around the world in different ways based on cultural differences, technological affordances, and other factors. When people go to search for “selfie” on Google Search, they are thinking different things as well. On Google Correlate, it is possible to identify the top correlating search terms that pattern-match the time patterns for the seeding search term. Based in this big data, these search term correlates (associated over extended time) provide a sense of the “group mind” around a particular topic.

scholarly journals Infodemiology of systemic lupus erythematous using Google Trends

Lupus ◽  
2017 ◽  
Vol 26 (8) ◽  
pp. 886-889 ◽  
Author(s):  
M Radin ◽  
S Sciascia
Keyword(s):  
Big Data ◽  
Northern Hemisphere ◽  
Lupus Erythematosus ◽  
Kendall Test ◽  
Google Trends ◽  
Data Monitoring ◽  
Search Term ◽  
Systemic Lupus ◽  
Search Terms ◽  
Google Search

Objective People affected by chronic rheumatic conditions, such as systemic lupus erythematosus (SLE), frequently rely on the Internet and search engines to look for terms related to their disease and its possible causes, symptoms and treatments. ‘Infodemiology’ and ‘infoveillance’ are two recent terms created to describe a new developing approach for public health, based on Big Data monitoring and data mining. In this study, we aim to investigate trends of Internet research linked to SLE and symptoms associated with the disease, applying a Big Data monitoring approach. Methods We analysed the large amount of data generated by Google Trends, considering ‘lupus’, ‘relapse’ and ‘fatigue’ in a 10-year web-based research. Google Trends automatically normalized data for the overall number of searches, and presented them as relative search volumes, in order to compare variations of different search terms across regions and periods. The Menn–Kendall test was used to evaluate the overall seasonal trend of each search term and possible correlation between search terms. Results We observed a seasonality for Google search volumes for lupus-related terms. In the Northern hemisphere, relative search volumes for ‘lupus’ were correlated with ‘relapse’ (τ = 0.85; p = 0.019) and with fatigue (τ = 0.82; p = 0.003), whereas in the Southern hemisphere we observed a significant correlation between ‘fatigue’ and ‘relapse’ (τ = 0.85; p = 0.018). Similarly, a significant correlation between ‘fatigue’ and ‘relapse’ (τ = 0.70; p < 0.001) was seen also in the Northern hemisphere. Conclusion Despite the intrinsic limitations of this approach, Internet-acquired data might represent a real-time surveillance tool and an alert for healthcare systems in order to plan the most appropriate resources in specific moments with higher disease burden.

scholarly journals Future orientation and fertility: cross-national evidence using Google search

2020 ◽  
Author(s):  
Nicolò Cavalli
Keyword(s):  
Web Search ◽  
Future Orientation ◽  
Fertility Rates ◽  
Fertility Decisions ◽  
Country Level ◽  
The World ◽  
Search Data ◽  
Quality Framework ◽  
Google Search ◽  
Cross National

Using digital traces to investigate demographic behaviours, I leverage in this paper aggregated web search data to develop a Future Orientation Index for 200 countries and territories across the world. This index is expressed as the ratio of Google search volumes for ‘next year’ (e.g., 2021) to search volumes for ‘current year’ (e.g., 2020), adjusted for country-level internet penetration rates. I show that countries with lower levels of future orientation also have higher levels of fertility. Fertility rates decrease quickly as future orientation levels increase; but at the highest levels of future orientation, this correlation flattens out. Theoretically, I reconstruct the role that varying degrees of future orientation might play in fertility decisions by incorporating advances in behavioural economics into a traditional quantity-quality framework à la Becker.

scholarly journals Semantics Discovery via Human Computation Games

Semantic Web ◽  
2013 ◽  
pp. 286-308 ◽  
Author(s):  
Jakub Šimko ◽  
Michal Tvarožek ◽  
Mária Bieliková
Keyword(s):  
Computer Games ◽  
Web Search ◽  
Human Computation ◽  
Search Term ◽  
Search Game ◽  
Search Terms ◽  
Qualitative Feedback ◽  
Novel Approach ◽  
Series Of Experiments ◽  
Relationship Network

The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.

scholarly journals Semantics Discovery via Human Computation Games

2011 ◽  
Vol 7 (3) ◽  
pp. 23-45 ◽  
Author(s):  
Jakub Šimko ◽  
Michal Tvarožek ◽  
Mária Bieliková
Keyword(s):  
Computer Games ◽  
Web Search ◽  
Human Computation ◽  
Search Term ◽  
Search Game ◽  
Search Terms ◽  
Qualitative Feedback ◽  
Novel Approach ◽  
Series Of Experiments ◽  
Relationship Network

The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.

scholarly journals International Real Estate Review

2020 ◽  
Vol 23 (2) ◽  
pp. 267-308
Author(s):  
Are Oust ◽  
◽  
Ole Martin Eidjord ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Search Term ◽  
Housing Bubble ◽  
Search Terms ◽  
Search Volume ◽  
Google Search ◽  
The U.S

The aim of this paper is to test whether Google search volume indices can be used to predict house prices and identify bubbles in the housing market. We analyze the data that pertain to the 2006?2007 U.S. housing bubble, taking advantage of the heterogeneous house price development in both bubble and non-bubble states in the U.S. Using 204 housing-related keywords, we test both single search terms and indices that comprise search term sets to see whether they can be used as housing bubble indicators. We find that several keywords perform very well as bubble indicators. Among all of the keywords and indices tested, the Google search volume for ¡§Housing Bubble¡¨ and ¡§Real Estate Agent¡¨, and a constructed index that contains the twelve best-performing search terms score the highest at both detecting bubbles and not erroneously detecting non-bubble states as bubbles. A new housing bubble indicator may help households, investors, and policy makers receive advanced warning about future housing bubbles. Moreover, we show that the Google search outperforms the well-established consumer confidence index in the U.S. as a leading indicator of the housing market.

scholarly journals Quality of Health Information on the Internet for Prostate Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Dwayne T. S. Chang ◽  
Robert Abouassaly ◽  
Nathan Lawrentschuk
Keyword(s):  
Prostate Cancer ◽  
Health Information ◽  
Health Resources ◽  
The Internet ◽  
Search Term ◽  
Search Terms ◽  
The Difference ◽  
The Government ◽  
Google Search

Introduction. To compare (1) the quality of prostate cancer health information on the Internet, (2) the difference in quality between websites appearing earlier or later in the search, and (3) the sources of sponsorship for each of these websites. Materials and methods. The top 150 listed websites on the Google search engine for each of the 11 search terms related to prostate cancer were analysed. Quality was assessed on whether the website conforms to the principles of the Health On the Net Foundation. Each of these websites was then reviewed to determine the main source of sponsorship. Statistical analysis was performed to determine if the proportion of HON accreditation varied among the different cohorts of listed websites and among the 11 search terms used. Results. In total, 1650 websites were analysed. Among these, 10.5% websites were HON-accredited. The proportion of HON-accredited websites for individual search terms ranged from 3.3% to 19.3%. In comparison with the search term of “Prostate cancer,” four search terms had statistically significant odds ratio of the rate of HON accreditation. Websites 51–150 were statistically less likely to have HON accreditation than websites 1–50. The top three website sponsors were journal/universities (28.8%), commercial (28.1%), and physician/surgeon (26.9%). Conclusions. The lack of validated and unbiased websites for prostate cancer is concerning especially with increasing use of the Internet for health information. Websites sponsored or managed by the government and national departments were most likely to provide impartial health information for prostate cancer. We need to help our patients identify valid and unbiased online health resources.

Prestige, Proximity, and Prejudice: How Google Search Terms Diffuse across the World

2019 ◽  
Vol 124 (5) ◽  
pp. 1496-1548 ◽  
Author(s):  
Christopher A. Bail ◽  
Taylor W. Brown ◽  
Andreas Wimmer
Keyword(s):  
Search Terms ◽  
The World ◽  
Google Search

scholarly journals What value can Google search data add to existing syndromic surveillance systems?

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Helen K. Green ◽  
Obaghe Edeghere ◽  
Alex Elliot ◽  
Ingemar Cox ◽  
Rachel McKendry ◽  
...  
Keyword(s):  
Public Health ◽  
Syndromic Surveillance ◽  
Added Value ◽  
Surveillance Systems ◽  
Search Term ◽  
Public Health Importance ◽  
Health Events ◽  
Search Terms ◽  
Search Data ◽  
Google Search

ObjectiveTo carry out an observational study to explore what added value Google search data can provide to existing routine syndromic surveillance systems in England for a range of conditions of public health importance and summarise lessons learned for other countries.IntroductionGlobally, there have been various studies assessing trends in Google search terms in the context of public health surveillance1. However, there has been a predominant focus on individual health outcomes such as influenza, with limited evidence on the added value and practical impact on public health action for a range of diseases and conditions routinely monitored by existing surveillance programmes. A proposed advantage is improved timeliness relative to established surveillance systems. However, these studies did not compare performance against other syndromic data sources, which are often monitored daily and already offer early warning over traditional surveillance methods. Google search data could also potentially contribute to assessing the wider population health impact of public health events by supporting estimation of the proportion of the population who are symptomatic but may not present to healthcare services.MethodsWe sought to determine the added public health utility of Google search data alongside established syndromic surveillance systems in England2 for a range of conditions of public health importance, including allergic rhinitis, scarlet fever, bronchitis, pertussis, measles, rotavirus and the health impact of heatwaves. Google search term selection was based on diagnostic and clinical codes underlying the syndromic indicators, with Google Trends3 used to identify additional related internet search terms. Daily data was extracted from syndromic surveillance systems2 and from the Google Health Trends Application Programming Interface (API) from 2012 to 2017 and a retrospective daily analysis undertaken during pre-identified public health events to identify a) whether signals were detected during these events and b) assess the correlation with analogous syndromic surveillance indicators through calculation of Spearman correlation coefficients and lag assessment to determine timeliness.ResultsWe detected increases in Google search term frequency during public health events of interest. Good correlation was seen with comparable syndromic surveillance indicators on a daily timescale for several health outcomes, including the search terms hayfever, scarlet fever, bronchiolitis and heatstroke. Weaker correlation was seen for conditions which occur in small numbers and are vaccine preventable such as measles and pertussis. Lag analysis showed similar timeliness between daily syndromic and Google data, suggesting that, overall, Google data did not provide an earlier or delayed signal compared to syndromic surveillance indicators in England.ConclusionsTo the best of our knowledge this is the first time trends in Google search data have been compared against syndromic data for a range of public health conditions in England. These findings demonstrate the potential utility of internet search query data in conjunction with existing systems in England, with syndromic surveillance data found to be as timely as Google data. These findings also have important implications for countries where there are no such healthcare-based syndromic surveillance systems in place. Factors to consider with analyses of Google search trend data in the context of disease surveillance have been highlighted, including the choice of search terms and interpretation of the reasons behind searching the internet.References1Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, Murugiah K. The use of google trends in health care research: a systematic review. PLoS One. 2014 Oct 22;9(10):e109583.2Public Health England. Syndromic surveillance: systems and analyses. 2017. Available online: https://www.gov.uk/government/collections/syndromic-surveillance-systems-and-analyses3Google. 2017. Google Trends. Available online:https://trends.google.com/trends/

Exploring Semantic Characteristics of Socially Constructed Knowledge Repository to Optimize Web Search

2013 ◽  
pp. 250-271
Author(s):  
Dengya Zhu ◽  
Heinz Dreher
Keyword(s):  
Web Search ◽  
Experimental Results ◽  
Training Data ◽  
Search Term ◽  
Short Term ◽  
User Perspective ◽  
Knowledge Repository ◽  
Search Results ◽  
Socially Constructed ◽  
Search Terms

Short-term queries preferred by most users often result in a list of Web search results with low precision from a user perspective. The purpose of this research is to improve the relevance of Web search results via search-term disambiguation and ontological filtering of search results based on socially constructed search concepts. A Special Search Browser (SSB) is developed where semantic characteristics of the socially constructed knowledge repository are extracted to form a category-document set. kNN is employed with the extracted category-documents as training data to classify Web results. Users’ selected categories are employed to present the search results. Experimental results based on five experts’ judgments over 250 hits from Yahoo! API demonstrate that utilizing the socially constructed search concepts to categorize and filter search results can improve precision by 23.5%, from Yahoo’s 41.7% to 65.2% of SSB based on the results of five selected ambiguous search-terms.

Infodemiological patterns in searching medication errors: relationship with risk management and shift work (Preprint)

2019 ◽  
Author(s):  
Fabio Fabbian ◽  
Emanuele Di Simone ◽  
Sara Dionisi ◽  
Noemi Giannetta ◽  
Luigi De Gennaro ◽  
...  
Keyword(s):  
Health Care ◽  
Risk Management ◽  
Shift Work ◽  
Medication Errors ◽  
Medical Errors ◽  
World Health ◽  
Noncommunicable Diseases ◽  
Western World ◽  
The World ◽  
Google Search

BACKGROUND Western world health care systems have been trying to improve their efficiency and effectiveness in order to respond properly to the aging of the population and the epidemic of noncommunicable diseases. Errors in drugs administration is an actual important issue due to different causes. OBJECTIVE Aim of this study is to measure interest in online seeking medical errors information online related to interest in risk management and shift work. METHODS We investigated Google Trends® for popular search relating to medical errors, risk management and shift work. Relative search volumes (RSVs) were evaluated for the period November 2008-November 2018 all around the world. A comparison between RSV curves related to medical errors, risk management and shift work was carried out. Then we compared world to Italian search. RESULTS RSVs were persistently higher for risk management than for medication errors during the study period (mean RSVs 74 vs. 51%) and RSVs were stably higher for medical errors than shift work during the study period (mean RSVs 51 vs 23%). In Italy, RSVs were much lower than the rest of the world, and RSVs for medication errors during the study period were negligible. Mean RSVs for risk management and shift work were 3 and 25%, respectively. RSVs related to medication errors and clinical risk management were correlated (r=0.520, p<0.0001). CONCLUSIONS Google search query volumes related to medication errors, risk management and shift work are different. RSVs for risk management are higher, are correlated with medication errors, and the relationship with shift work appears to be even worse, by analyzing the entire world. In Italy such a relationship completely disappears, suggesting that it needs to be emphasized by health care authorities.

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