Tweet, but Verify: Epistemic Study of Information Verification on Twitter

While Twitter provides an unprecedented opportunity to learn about breaking news and current events as they happen, it often produces skepticism among users as not all the information is accurate but also hoaxes are sometimes spread. While avoiding the diffusion of hoaxes is a major concern during fast-paced events such as natural disasters, the study of how users trust and verify information from tweets in these contexts has received little attention so far. We survey users on credibility perceptions regarding witness pictures posted on Twitter related to Hurricane Sandy. By examining credibility perceptions on features suggested for information verification in the field of Epistemology, we evaluate their accuracy in determining whether pictures were real or fake compared to professional evaluations performed by experts. Our study unveils insight about tweet presentation, as well as features that users should look at when assessing the veracity of tweets in the context of fast-paced events. Some of our main findings include that while author details not readily available on Twitter feeds should be emphasized in order to facilitate verification of tweets, showing multiple tweets corroborating a fact misleads users to trusting what actually is a hoax. We contrast some of the behavioral patterns found on tweets with literature in Psychology research.Comment: Pre-print of paper accepted to Social Network Analysis and Mining (Springer

Crisis communication capacity for disaster resilience: community participation of information providing and verifying in Indonesian volcanic eruption

This study investigates information networks during the 2010 Merapi volcanic eruption, as a well-proven representative case to capture the capacity of local communities to provide, share, and verify information. Abstract Strengthening community capacities is important to significantly increase community resilience after a shock. In the phase of disaster resilience, relief activities generally are focused on aid distribution, physical and economic recovery to stabilize the affected community. Yet, building the community capacity for crisis communication has not been prioritized; meanwhile it can accelerate the social capital in disaster resilience. By selecting Jalin Merapi (Merapi Circle Information Networks) in the 2010 Merapi eruption as a case study; this study captures how local communities can empower themselves through participation in providing, sharing, and verifying the information within their social network. Data has been collected by in-depth interviews with the local communities‟ members and focus-groups with appointed officials in Merapi volcano. Jalin Merapi has developed a collaborative system with community radio stations and local communities as reliable information sources and direct verifiers. A media convergence of 14 communication technologies enables a broad spread of information about refugees‟ real needs within and beyond the local communities. As the result, the refugees could receive adequate aid based on their current situation and culture. Hence, they can quickly recover themselves and furthermore foster the resilience process within the affected communities in general. Finally, this study is trying to acknowledge the challenges for strengthening the community capacity for crisis communication with bottom-up approaches, based on their knowledge and vulnerabilities in disaster resilience

INVESTIGATION OF DEFORESTATION USING MULTI-SENSOR SATELLITE TIME SERIES DATA IN NORTH KOREA

Department of Urban and Environmental Engineering(Environmental Science and Engineering)North Korea is very vulnerable to natural disasters such as floods and landslides due to institutional, technological, and other various reasons. Recently, the damage has been more severe and vulnerability is also increased because of continued deforestation. However, due to political constraints, such disasters and forest degradation have not been properly monitored. Therefore, using remote sensing based satellite imagery for forest related research of North Korea is regarded as currently the only and most effective method. Especially, machine learning has been widely used in various classification studies as a useful technique for classification and analysis using satellite images. The aim of this study was to improve the accuracy of forest cover classification in the North Korea, which cannot be accessed by using random forest model. Indeed, another goal of this study was to analyze the change pattern of denuded forest land in various ways. The study area is Musan-gun, which is known to have abundant forests in North Korea, with mountainous areas accounting for more than 90%. However, the area has experienced serious environmental problems due to the recent rapid deforestation. For example, experts say that the damage caused by floods in September 2016 has become more serious because denuded forest land has increased sharply in there and such pattern appeared even in the high altitude areas. And this led the mountain could not function properly in the flood event. This study was carried out by selecting two study periods, the base year and the test year. To understand the pattern of change in the denuded forest land, the time difference between the two periods was set at about 10 years. For the base year, Landsat 5 imageries were applied, and Landsat 8 and RapidEye imageries were applied in the test year. Then the random forest machine learning was carried out using randomly extracted sample points from the study area and various input variables derived from the used satellite imageries. Finally, the land cover classification map for each period was generated through this random forest model. In addition, the distribution of forest changing area to cropland, grassland, and bare-soil were estimated to the denuded forest land. According to the study results, this method showed high accuracy in forest classification, also the method has been effective in analyzing the change detection of denuded forest land in North Korea for about 10 years.ope