Under Review

Government 2.0 Explained

Gohar Feroz Khan

Although it seems that Government 2.0 will finally deliver the promise of a truly transparent government, many practitioners around the globe (particularly those in the developing world) are reluctant or unable to develop strategies and allocate resources to Government 2.0. As a result, governments around the world ignore or mishandle the opportunities and threats presented by Government 2.0. The primary reason underlying this behavior is the lack of understanding regarding Government 2.0. The purpose of the study is to address this gap in knowledge and understanding by presenting and illustrating fundamental concepts of Government 2.0. A web survey of 200 government website from 40 countries (20 each from advanced and developing countries) and 45 Web 2.0 initiatives across the globe was used to present and illustrate fundamental concept of the Government 2.0. We suggested a three stage Government 2.0 Utilization Model (GUM) starting from information socialization (stage 1), and then moving on to mass collaboration (stage 2), and social transaction (stage 3). Based on the web survey, we also suggested three Government 2.0 implementation scenarios (i.e., standalone, nested, and hybrid implementation). The study will help researchers and practitioners in understanding the Government 2.0 phenomenon and the opportunities presented by it.

Keywords: Government 2.0, Social Media, Government 2.0 utilization model, Government 2.0 implementation scenarios, and Government 2.0 relationships

Why some content go viral on social media? An exploratory study

Khan, G.F., & Sokha, W.

In this research, we sought reasons for some content (mainly videos) going viral on social media. Using YouTube APIs and Webometrics analyst tool, we collected data on about 100 (all time) most viewed YouTube videos and information about the users associated with the videos. We constructed and tested an empirical model to understand the relationship among users’ social and network characteristics (e.g. user age, gender, location, view count, subscriber, join date, total videos posted), video characteristics (post date, duration, and type), external network capital (in-links and hit counts), and viral constructs (likes, dislikes, favorite count, view count, and comment count) . SPSS correlations, multiple regression analysis, and Webometric analysis were used to explore the association among the constructs. Among other findings, our results show that popularity of the videos was not only the function of YouTube system par se, but that network dynamics (e.g. in-links and hits counts) and offline social capital (e.g., fan base and fame) play crucial roles in the viral phenomenon, particularly view count.

-Khan G. F., Mark H., Tomasz M., (work in progress), Best Practices in Social Media at Non-profit, Public, Education, and Healthcare Organizations, A special issue of Social Science Computer Review (SSCR) Journal

-Khan G.F., & Sokha, W., (under review 1st round). Why some content go viral on social media? an exploratory study, Abstract

-Khan, G.F., (under review). Govt. 2.0 Explained. Abstract

-Khan, G. F., Kon. S. L., (working paper). SNS Usage in GRIs: A Risk-Benefit analysis, working paper.

-Sokha W., Khan, G. F.(working paper). Social Media Adoption: A cost-benefit analysis framework, working paper.