- Volume 16 Issue 4
Using bigdata analysis procedures, the present study sought to review and explore the various aspects of self-disclosure and boundary impermeability of worldwide twitter users. A total of 415 million tweets issued by 54 million users were collected during 6 months and the users of top 10 languages were investigated. And the effect of languages of twitter users on the boundary impermeability, disclosure rate of user profile, profile image, geographical information, URL in profile and user description were analyzed in this study. The results showed that the boundary impermeability and all the self-disclosure rates of twitter users (profile, profile image, geographical information, URL in profile, user description) were significantly (p<0.001) different among language groups of users. The self-disclosure rates and the average points of Portuguese, Indonesian and Spanish users were higher than those of Arabic, Japanese, Turkish and Korean users. The results also showed a positive relationship between boundary impermeability and the number of tweets (including retweets) issued by each users.
Self-Disclosure;Boundary Impermeability;Twitter Users;SNS
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