• The Korean Journal of Archival Studies
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• no.17
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• pp.247-292
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• 2008

Investigations have been started to set the modern history and national spirit to rights after Commissions were established. Those Commissions are established and operated with time limit to finish its own missions. They creates three kinds of records as acquired materials which acquired or are donated for investigation; investigation records as investigation reports; and administrative records that created while supporting organization's operation. The Commissions use more past records to do special tasks asnation's slate clean and uncovering the truth than other agencies. In other words, the commissions take the most advantages of well-managed records, however, their record management environment and operation systems are relatively loose than other permanent machineries. It has three reasons that; first, there is no record management regulations and criteria for machineries that have time limit. This affected each commissions 'systems and 6 Truth Commissions' record management systems are built separately and on the different level; Second, members lack responsibility from frequent sending, reinstatement, change, and restructuring and that makes troubles to produce and manage records; Third, central archives pay less attention to machineries that operated limited period as the truth commissions. The Commissions rather need more systematic control because its records have historical value. To solve these problems, record management regulations have to be prepared first with features of organizations running limited time and commissions' records as acquired materials or investigation records. Furthermore, building up standard record management system for the Commissions, standardizing transfer data, imposing professional record personnel, and setting limits frequent personnel changes would finish practical problems. Besides, those records created to reveal the truth should use for education and research because Truth Commissions are established to set unfortunate history right and not to repeat it again. The records would serve as steppingstone for establishment of the Truth Record Center that does education, information work, publication, and research with the records. The record center would help using the records efficiently and improving knowledge for its people. And, the center should devote people to recognize importance of the records.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.