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This study investigates the popularity, global and local presence of the top cryptocurrency websites in terms of market capitalization, and geographic distribution of cryptocurrency information on the web by mapping the information network of cryptocurrency sites. The study also explores whether web traffic and social network metrics serve as valuable indicator of financial performance of cryptocurrencies. Both citation and social network analyses were employed. The results suggest that bitcoin.org, bitcoin.com and steemit.com are the most popular sites based on the number of hit counts. Information production and consumption about coins are concentrated in European and Asia–Pacific regions. Germany and technology startup companies are the most central sources for cryptocurrency-related information in the network. This study also found positive cross correlation outcomes between web traffic, social network attributes, and cryptocurrency performance indicators. The finding demonstrates that the number of TLDs and multiple social network centrality measures are useful indicators of cryptocurrency market capitalization, trading volume, and price.

Many studies have examined citizen participation in policymaking and its delivery mechanisms through social media tools such as Facebook, Twitter, and YouTube, but few have explored empirical strategies to investigate the nature of online citizen participation in the field of policy analysis and management. The webometric approach is a quantitative tool for capturing network-based intercommunication derived from the Web 2.0 sphere as user-generated content by using diverse methods in informetrics. By applying this approach to examine citizen participation on social media, this study introduces an empirical strategy for collecting data on social media tools used by governments and identifies patterns of citizens’ e-participation and relationships between citizens, governments, and various organizations involved in policymaking processes through social media. The results based on the 311 service platforms of New York City and San Francisco suggest that the webometric approach can not only extract government agencies’ communication behaviors toward others on social media but also capture the overall network structure, the pattern of interactions between participants, and network properties of participants.