An Entrance for the Uninterested: Who Watches Soft News and How Does It Affect Their Political Participation?

As soft news shows in television present politics in an entertaining format, they are likely to attract and grab the attention of people who do not have a high interest in politics. Consequently, soft news might mobilize these citizens to engage in politics. This study tests this potential by using a 2-wave panel survey among a national sample of voters (N = 2,680) collected in relation to the 2015 National Election in Denmark. The results show that people with lower political interest were indeed more likely to increase their use of soft news during the election campaign and that, as a consequence, these low-motivated people also increased their passive participation, such as seeking additional information about the election. Further, the results show that this type of passive participation is likely to function as a stepping-stone to active forms of participation, such as attending political events or contacting politicians.     

The effects of gain versus loss framing and issue involvement on publics’ responses to nuclear energy messages in South Korea

This study investigates how the public’s perceptions of nuclear power, one of the modern technologies at the center of public debate on risk issues, are influenced by gain versus loss framing in the volatile context of nuclear energy applications in South Korea. Drawing upon prospect theory as its conceptual framework, this experiment using 566 adult participants found that loss-framed messages (i.e. emphasizing the negative outcomes of not using nuclear power) were more effective in increasing participants’ message credibility perceptions as compared to gain-framed messages (i.e. emphasizing the positive outcomes of using nuclear power). Additionally, the results found issue involvement to be a significant moderator of the framing effect, by demonstrating that the advantage of loss framing was stronger for participants who were highly involved in nuclear energy issue, as compared to those who were less involved in the issue. The theoretical and practical implications of these findings are discussed.     

XMage: An image retrieval method based on partial similarity

XMage is introduced in this paper as a method for partial similarity searching in image databases. Region-based image retrieval is a method of retrieving partially similar images. It has been proposed as a way to accurately process queries in an image database. In region-based image retrieval, region matching is indispensable for computing the partial similarity between two images because the query processing is based upon regions instead of the entire image. A naive method of region matching is a sequential comparison between regions, which causes severe overhead and deteriorates the performance of query processing. In this paper, a new image contents representation, called Condensed eXtended Histogram (CXHistogram), is presented in conjunction with a well-defined distance function CXSim() on the CX-Histogram. The CXSim() is a new image-to-image similarity measure to compute the partial similarity between two images. It achieves the effect of comparing regions of two images by simply comparing the two images. The CXSim() reduces query space by pruning irrelevant images, and it is used as a filtering function before sequential scanning. Extensive experiments were performed on real image data to evaluate XMage. It provides a significant pruning of irrelevant images with no false dismissals. As a consequence, it achieves up to 5.9-fold speed-up in search over the R*-tree search followed by sequential scanning.