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Social media connect individuals in different geographical location and allow people of different political and cultural backgrounds to discuss and participate in events that occur in distant corners of the globe. But, this does not suggest that social media promote homogeneous globalization. Rather, the local and its interactions with the global or regional views remain a powerful force in the realm of social media. The purpose of this paper is to take on the local/global factors in the social media service Twitter and analyzed the keyword-captured Chinese language tweets relating to the 2012 presidential election in Taiwan.

Language code usage was used to sort out the community origins of Chinese language tweets relating to the election, given that distinct types and codes of Chinese characters are used within each political border. Community-specific patterns of communication were identified by cross-correlating language styles, tweeting frequency and participating users. Social network analysis was used to further characterize the local factors in the global social media.

The authors found that the language styles and character types can be used to identify the regions to which the users belong. The authors were able to identify community-specific patterns of communication and reconstruct a social network that exhibits local characteristics.

The results demonstrate that language code can be used to identify the community origin of Chinese tweets. This will enable fine-grain content-based analysis of the Chinese language social media.

The purpose of this paper is to extend the technology readiness and acceptance model (TRAM) to consider an individual’s health consciousness (HC), thereby improving the capability of the model to predict an individual’s attitude toward and intention to download and use dietary and fitness apps.

A total of 994 participants completed a self-reported online questionnaire. Structural equation modeling and χ² difference testing were conducted to compare the predictive capability of the proposed health consciousness TRAM (HC-TRAM) and the TRAM. The comparison of the proposed HC-TRAM in terms of potential and actual users of dietary and fitness apps was also discussed.

The results obtained from the HC-TRAM and the TRAM indicate that in addition to technology readiness, HC exerts a positive effect on the perceived ease of use and usefulness of dietary and fitness apps. χ² difference test results indicated that the predictive capability of the proposed HC-TRAM is higher than that of the TRAM.

The drivers and inhibitors of a person’s readiness to embrace modern information technology play roles when predicting his or her intention to download and use dietary and fitness apps. HC should be promoted by encouraging people to eat right and regularly perform appropriate exercise to prevent obesity and overweight, thereby maintaining a healthy lifestyle.

This study incorporated individual cognitive factors and HC into the TRAM to fill the literature gap and deepen and broaden existing theoretical frameworks of the TRAM in the public health sector.