Forecasting private consumption with Google Trends data

2018 ◽  
Vol 38 (2) ◽  
pp. 81-91 ◽  
Author(s):  
Jaemin Woo ◽  
Ann L. Owen
Keyword(s):  
Private Consumption ◽  
Google Trends

scholarly journals Forecasting private consumption: survey-based indicators vs. Google trends

2011 ◽  
Vol 30 (6) ◽  
pp. 565-578 ◽  
Author(s):  
Simeon Vosen ◽  
Torsten Schmidt
Keyword(s):  
Private Consumption ◽  
Google Trends ◽  
Consumption Survey

Produktivkraft als Versprechen

2016 ◽  
Vol 46 (185) ◽  
pp. 621-638 ◽  
Author(s):  
Christian Siefkes
Keyword(s):  
Private Consumption ◽  
Minor Role ◽  
Progressive Reduction ◽  
Internal Forces ◽  
A Minor

The ‘Fragment on Machines’ from Marx’s Grundrisse is often cited as an argument that the internal forces of capitalism will lead to its doom. But the argument that the progressive reduction of labor must doom capitalism lacks a proper foundation, as a comparison with the ‘Schemes of Reproduction’ given in Capital II shows. The latter, however, aren’t fully convincing either. In reality, more depends on the private consumption of capitalists than either model recognizes. Ultimately, most can be made of the ‘Fragment on Machines’ by reading it not as an exposure of capitalism’s internal contractions, but as a discussion of a possible communist future where labor (or work) will play but a minor role.

An Epidemic Avian Influenza Prediction Model Based on Google Trends

2019 ◽  
Vol 16 (4) ◽  
pp. 303-310 ◽  
Author(s):  
Yi Lu ◽  
Shuo Wang ◽  
Jianying Wang ◽  
Guangya Zhou ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Avian Influenza ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Google Trends ◽  
Health Providers ◽  
Human Beings ◽  
Success Rates ◽  
New Model ◽  
Regression Approach

The occurrence of epidemic avian influenza (EAI) not only hinders the development of a country's agricultural economy, but also seriously affects human beings’ life. Recently, the information collected from Google Trends has been increasingly used to predict various epidemics. In this study, using the relevant keywords in Google Trends as well as the multiple linear regression approach, a model was developed to predict the occurrence of epidemic avian influenza. It was demonstrated by rigorous cross-validations that the success rates achieved by the new model were quite high, indicating the predictor will become a very useful tool for hospitals and health providers.

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

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.

Public Awareness of Preventive Measures against COVID-19: A Google Trends Analysis (Preprint)

2020 ◽  
Author(s):  
Alex Mok ◽  
Oliver Oi Yat Mui ◽  
Kwan Pui Tang ◽  
Chi-Fai NG ◽  
Sunny Hei Wong ◽  
...  
Keyword(s):  
Public Health ◽  
Temporal Trend ◽  
Preventive Measures ◽  
Public Awareness ◽  
Google Trends ◽  
Online Searching ◽  
Effective Measure ◽  
Heat Maps ◽  
Hand Sanitizer ◽  
Incidence Data

BACKGROUND The 2019 coronavirus pandemic (COVID-19) has led to increase in global awareness of related public health preventive measures. The public awareness can be reflected by online searching trends of major search engines, namely Google Trends. OBJECTIVE This study aims to interpret online searches of COVID-19 related public health preventive measures and to identify possible correlations between early search trends and progression of the pandemic. METHODS Search data from five queries “Mask”, “Hand Washing”, “Social Distancing”, “Hand Sanitizer”, and “Disinfectant” were extracted from Google Trends (GT) in the form of Relative Search Volumes (RSV). Global incidence data of COVID-19 was obtained from January 1st to June 30th 2020. Subsequently, the data were analyzed and illustrated in forms of a global temporal RSV trend diagram, a geographical RSV distribution chart, scatter graphs comparing regional RSV with average daily cases; and heat-maps comparing temporal trend of RSV with average daily cases. RESULTS Global temporal trend revealed multiple surges in RSV, which were temporally associated with certain COVID news events. Geographical distribution showed differences of query interests among regions. Although scatter graphs failed to illustrate strong correlations between regional RSV and average daily cases, the heat-maps were able to demonstrate patterns of early RSV peaks in countries with lower average daily cases, for queries “Mask”, “Hand Sanitizer”, and “Disinfectant”, upon incorporating with the temporal element into analysis. CONCLUSIONS Early public awareness of multiple preventive measures was observed in countries with lower daily average cases. Public health authorities may look into early public awareness as an effective measure for future disease control.

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