Emergence, Evolution and Scaling of Online Social Networks

This work was partially supported by AFOSR under Grant No. FA9550-10-1-0083, NSF under Grant No. CDI-1026710, NSF of China under Grants Nos. 61473060 and 11275003, and NBRPC under Grant No. 2010CB731403. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Utilization of Crowdsourced Maps in Catastrophic Disasters

Crowdsourced data, the collective messages from citizens through social media like Twitter® or Facebook®, have been increasingly recognized as a vital information source in a catastrophic disaster. Because there is often insufficient emergency personnel to gather situational information during a big disaster, the crowdsourced data can offer a supplemental means for data collection or dissemination immediately after the disaster. In addition, crowdsourced maps can empower citizens with their involvement. In the Haiti earthquake of 2010, crowdsourced data was first used to create a web map application to aid the humanitarian effort. With some success in Haiti, these crowdsourced maps have since been created for other disasters in many countries. However, although the crowdsourced map showed great potential, it also revealed a major shortcoming: most first responders did not use the crowdsourced map. This thesis addresses the issues associated with using crowdsourced maps in the responder community and seeks a possible solution for increasing utilization by first responders during catastrophic disasters. Citizen messages from the Japan earthquake of 2011 were analyzed and filtered by categories best suited for responders. Then, considering the technological difficulties experienced immediately following the disaster, the best communication means were explored to complete two-way communication between responders and citizens

Connecting the Last Mile: The Role of Communications in the Great East Japan Earthquake

This report, set against the backdrop of a highly developed communications infrastructure, highlights the specific role that communications played in both survival and recovery in the hours, days, weeks and months after the Great East Japan Earthquake occurred. It does not focus on the handling of information related to the Fukushima nuclear disaster by the Tokyo Electric Power Company (TEPCO) and the Japanese Government, as this issue - however important - has already received great attention.Connecting the Last Mile explores, rather, how communities in the most devastated areas of the prefectures of Iwate, Miyagi and Fukushima got their information. It identifies which communications channels were used before, during and after the earthquake and tsunami, and it attempts to answer a central question: what are the lessons learned about communications with disaster-affected populations from the megadisaster, not only for Japan but for the international community of humanitarian responders

Why I Retweet? Exploring User’s Perspective on Decision-Making of Information Spreading during Disasters

The extensive use of social media during disasters raises an important issue concerning use of social media to spread information, including misinformation. This study explores the underlying behavioral context of disaster information sharing by Twitter users. We conducted a web survey with 999 respondents in Japan to determine what makes people retweet disaster information in disaster situations. As a result of factor analysis, four factors were identified from 36 questions, namely: 1) Willingness to provide relevant and updated information because the information is believable, 2) Want people to know the information they perceive as important, 3) Retweeter subjective feelings and interests, and 4) Want to get feedback and alert other people. The results suggest that two of the factors influenced different groups of people in the community differently; however, everybody can play their role to reduce the negative impact of social media used for future disaster. Based on the findings, we discuss practical and design implications of social media use during disasters

“Tutteli to Japan”: A case study of spontaneous collaboration in disaster response

“Tutteli to Japan” (TTJ) is a case study of ordinary people, a group of Japanese women living in Finland, trying to figure out how to help disaster-affected citizens from a distance in coordination with likeminded strangers on-the-ground to accomplish aid supply delivery. Unlike commonly seen in citizen response to disasters, this case did not start as an extension of pre-existing social group activities or an informal group of volunteers under the name of TTJ. Rather, the effort emerged from individual responses on the Internet to the 2011 Great Tohoku Earthquake and Tsunami disasters in Japan, expressing their compassions and aspirations to do something for the disaster victims; some were on Twitter, some were on their blogs. As the devastation escalated, so did the people’s eagerness to do something about the inadequate distribution of resources, with a focus on the breastfeeding mothers in Japan who only had access to powder-based baby formula. Having this challenge left untouched by government or aid agencies, these concerned individuals, as novice learners of international aid work without a chain of command, continued seeking and sharing information in order to deliver the liquid baby formula regardless of informational, operational, and situational uncertainties surrounding them. Within the next forty days, these volunteer individuals were able to ship six times, a total of 12,000 cartons of formula, directly delivered and distributed to the hands of breastfeeding mothers in twelve different locations in the disaster-affected communities in Japan. In this dissertation, I study the entangled, mutually collaborative nature of finding a way to help processes within and between like-minded individuals and the broader context of people and information with emphasis on information needs and learning. Drawing on a dataset that encompasses a range of real-time social media data as well as interviews and documentation, this single-case study traces how ordinary citizens interacting online develop the idea for delivery of baby formula as emergency supplies and how these like-minded strangers collaboratively mobilized resources for the TTJ logistics and processes of packaging, dispatching and delivering large volumes of relief supply including: the fundraising volunteers in Finland, the drivers and distributors in Japan. This study aims to describe how such ordinary people’s information interactions shape spontaneous collaboration in disaster response. My findings suggest that independent public participation and collaborative efforts for disaster response perform as sources of tensions and various kinds of vagueness, but these are the functions that spontaneous volunteers can offer resourcefully. With learning by doing approaches, these compassionate individuals, both online and on-the-ground, muddled through unknown needs of unfamiliar activities in identifying, managing and processing different kinds of tasks, particularly by asking for information and acting on information received including uses of vague language and uncertain sources of information. This iteration of dual processes – searching for information to help and self-organizing under leaderless management – illuminates underlying processes of spontaneous collaboration. I argue that the TTJ illustrates the power of intention, which is the power of creativity among ordinary people acting on information processed through humane-driven technology use. These iterative information interactions can be best understood through a new concept articulated in this dissertation, shared uncertainty. This concept encompasses our understanding of independent public participation and collaboration and offers an interdisciplinary bridge between research in information behavior, computer-supported cooperative work, crisis informatics and disaster studies

How can Big Data from Social Media be used in Emergency Management? A case study of Twitter during the Paris attacks

Postponed access: the file will be accessible after 2019-06-11Over the past years, social media have impacted emergency management and disaster response in numerous ways. The access to live, continuous updates from the public brings new opportunities when it comes to detecing, coordinating and aiding in an emergency situation. The thesis present a research of social media during an emergency situation. The goal of the study is to discover how data from social media can be used for emergency management and determine if existing analysis services can be proven useful for the same occasion. To achieve the goal, a dataset from Twitter during the Paris attacks 2015 was collected. The dataset was analyzed using three different analysis tools; IBM Watson Discovery service, Microsoft Azure Text Analytics and an own developed Keyword Frequency Script. The results indicate that data from social media can be used for emergency management, in form of detecting and providing important information. Additional testing with larger datasets is needed to fully demonstrate the usefulness, in addition to interviews with emergency responders and social media users.Masteroppgave i informasjonsvitenskapINFO39

Facts and Fabrications about Ebola: A Twitter Based Study

Microblogging websites like Twitter have been shown to be immensely useful for spreading information on a global scale within seconds. The detrimental effect, however, of such platforms is that misinformation and rumors are also as likely to spread on the network as credible, verified information. From a public health standpoint, the spread of misinformation creates unnecessary panic for the public. We recently witnessed several such scenarios during the outbreak of Ebola in 2014 [14, 1]. In order to effectively counter the medical misinformation in a timely manner, our goal here is to study the nature of such misinformation and rumors in the United States during fall 2014 when a handful of Ebola cases were confirmed in North America. It is a well known convention on Twitter to use hashtags to give context to a Twitter message (a tweet). In this study, we collected approximately 47M tweets from the Twitter streaming API related to Ebola. Based on hashtags, we propose a method to classify the tweets into two sets: credible and speculative. We analyze these two sets and study how they differ in terms of a number of features extracted from the Twitter API. In conclusion, we infer several interesting differences between the two sets. We outline further potential directions to using this material for monitoring and separating speculative tweets from credible ones, to enable improved public health information.Comment: Appears in SIGKDD BigCHat Workshop 201