Supporting effective health and biomedical information retrieval and navigation: A novel facet view interface evaluation

AbstractThere is a need to provide a more effective user interface to facilitate non-domain experts’ health information seeking in authoritative online databases such as MEDLINE. We developed a new topic cluster based information navigation system called SimMed. Instead of offering a list of documents, SimMed presents users with a list of ranked clusters. Topically similar documents are grouped together to provide users with a better overview of the search results and to support exploration of similar literature within a cluster. We conducted an empirical user study to compare SimMed to a traditional document list based search interface. A total of 42 study participants were recruited to use both interfaces for health information exploration search tasks. The results showed that SimMed is more effective in terms of users’ perceived topic knowledge changes and their engagement in user-system interactions. We also developed a new metric to assess users’ efforts to find relevant citations. On average, users need significantly fewer clicks to find relevant information in SimMed than in the baseline system. Comments from study participants indicated that SimMed is more helpful in finding similar citations, providing related medical terms, and presenting better organized search results, particularly when the initial search is unsatisfactory. Findings from the study shed light on future health and biomedical information retrieval system and interface designs

Finding and exploring memes in social media

Critical literacy challenges us to question how what we read has been shaped by external context, especially when infor-mation comes from less established sources. While cross-checking multiple sources provides a foundation for critical literacy, trying to keep pace the constant deluge of new on-line information is a daunting proposition, especially for ca-sual readers. To help address this challenge, we propose a new form of technological assistance which automatically discovers and displays underlyingmemes: ideas embodied by similar phrases which are found in multiple sources. Once detected, these underlying memes are revealed to users via generated hypertext, allowing memes to be explored in con-text. Given the massive volume of online information today, we propose a highly-scalable system architecture based on MapReduce, extending work by Kolak and Schilit [11]. To validate our approach, we report on using our system to pro-cess and browse a 1.5 TB collection of crawled social media. Our contributions include a novel technological approach to support critical literacy and a highly-scalable system archi-tecture for meme discovery optimized for Hadoop [25]. Our source code and Meme Browser are both available online

Mysterious Influential Users in Political Communication on Twitter: Users' Occupation Information and Its Impact on Retweetability

This study attempts to examine the effect of user’s self-disclosed identification to measure his influence and activity on Twitter. By looking at the most frequently shared top 1076 tweets written by 250 users during the 2012 presidential election campaign South Korea, we particularly examine the relation between user’s occupation information and the measures of his ‘influence’: the number of followers and number of retweets by others. Influential users in South Korean political communication network on Twitter are classified as one group with self-disclosed occupation information and the other group without that information. User’s occupation information clearly shows the impact on the number of followers for both groups. On the other hand, user group without self-disclosed occupation information has a higher level of producing influential political tweets and wide retweetability over the other group, regardless the small number of followers. It suggests that further study needs to identify other variables that may influence particular user or tweet’s retweetability as an indicator of influence.ye

Citizens' use of Twitter in political information sharing in South Korea

This study examined citizens’ use of social networking site Twitter in political information sharing in South Korea. Content analysis was used in classifying message types and sentiments from the most frequently re-tweeted (RT) messages including the names of three top political leaders running for general elections in 2012. Correlation analysis comparing citizens’ use of Twitter in political information sharing online with results of public opinion polls offline indicated: 1) the volume and magnitude of re-tweeted messages are significantly correlated with results of public opinion polls; 2) types of messages are not correlated with the public opinion polling results; 3) positive and negative sentiment revealed in Twitter messages are highly correlated with the results of public opinion polls. Findings from this case study provide insights into citizens’ use of Twitter in political communication.published or submitted for publicationis peer reviewe