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Author: Admin | 2025-04-28
To obtain information about the users from IP addresses and Bitcoin client downloads. Indeed, the first IP address is a noisy identification of the origin of the transaction, while Bitcoin Core is not the only Bitcoin client in use and might give a partial picture of overall Bitcoin adoption. In order to check if they give a consistent picture of Bitcoin adoption, we study the correlation between the two time series and after removing small fluctuations by applying a moving window average (window length: 1 month, offset: 1 day), we indeed measure a high correlation (Table 4). The fact that they correlate positively even though they potentially concern different users encourages the use of these data sources as proxy for the distribution of users among countries. Additionally, we compute the Spearman correlation coefficient between the ranking of countries given by IP addresses and client downloads in three different years, arriving to the same conclusion. Table 4 Correlation between Google Trends time series, number of unique IPs and Bitcoin client downloads. Here we report correlations between the time-series at world level, and the average correlation at country level, during the period from March 2012 to May 2014. Moreover, selecting a period of one year we compute the Spearman correlation between the countries, ranked using the three proxiesFull size tableWe also confronted the Google Trends time series with the numbers of unique IPs and client downloads computing the pairwise Pearson correlations. Given the high correlations as shown in Table 4, we conclude that the Google Trends time series may also be used as an indicator of the country Bitcoin adoption. We suppose that this assumption holds for the whole Google Trends data collection period that is longer than for other data sources. This allows us to discuss long term adoption trends of the selected countries.To assess the relevance of the use of Bitcoin search time series for comparing country adoption, we also measured the Spearman correlation between the pairwise rankings of countries by Bitcoin searches, number of Bitcoin clients downloaded and new IPs appearing. Correlations are also high, apart for the year 2012 where the signal about Bitcoin searches is too low for allowing comparison between countries. Moreover the country ranking based on Google queries heavily depends on Google usage by country, which can be very heterogeneous. As there is no trivial normalization to compensate the heterogeneity of Google usage within countries we will not use the rank provided by sorting Google Trends by countries.3.2 Adoption trends: developing versus developed countriesUsing the data from Google Trends we studied the evolution of the collective attention by country from 2009 to early 2017. As we are interested in the long term trends, we smoothed the Bitcoin search time series by country using a low-pass filter to focus on variation on a time scale of 3 years. To study the main trends present in the time series, we built a matrix \(A \in \mathbb{R}^{n \times m}\) (where n represents the number of countries and m
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