Combining Big Social Media Data and FCA for Crisis Response

The use of social media is now prevalent in all aspects of society. Each and every major news event is accompanied by a stream of real-time social media posts, creating a vast and ever changing data supply - a hallmark of big data. The aim of the ATHENA project is to turn this stream of information into a vital resource for the public and first responders during a crisis. ATHENA recognizes that citizens are currently under-utilized in crises and that they are often willing to engage in the response effort. Social media provides a robust platform for this interaction. Due to the volume and fast paced nature of the incoming data streams, the challenges for ATHENA system are how to integrate and process this data and then how to transform it into intelligence to be used by law enforcement agencies and the public alike. This paper introduces potential applications within the ATHENA project, in particular, those based on a technique known as formal concept analysis

Tweet Factors Influencing Trust and Usefulness During Both Man-Made and Natural Disasters

ABSTRACT To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the usefulness of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, in this paper, we characterize tweets, which are perceived useful or trustworthy, and determine their main features. Our analysis is carried out on two datasets (one natural and one man made) gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a high correlation and similar factors (support for the victims, informational data, use of humor and type of emotion used) influencing trustworthiness and usefulness for both disaster types. This could have impacts on how messages from social media data are analyzed for use in crisis response

Inferring the Origin Locations of Tweets with Quantitative Confidence

Social Internet content plays an increasingly critical role in many domains, including public health, disaster management, and politics. However, its utility is limited by missing geographic information; for example, fewer than 1.6% of Twitter messages (tweets) contain a geotag. We propose a scalable, content-based approach to estimate the location of tweets using a novel yet simple variant of gaussian mixture models. Further, because real-world applications depend on quantified uncertainty for such estimates, we propose novel metrics of accuracy, precision, and calibration, and we evaluate our approach accordingly. Experiments on 13 million global, comprehensively multi-lingual tweets show that our approach yields reliable, well-calibrated results competitive with previous computationally intensive methods. We also show that a relatively small number of training data are required for good estimates (roughly 30,000 tweets) and models are quite time-invariant (effective on tweets many weeks newer than the training set). Finally, we show that toponyms and languages with small geographic footprint provide the most useful location signals.Comment: 14 pages, 6 figures. Version 2: Move mathematics to appendix, 2 new references, various other presentation improvements. Version 3: Various presentation improvements, accepted at ACM CSCW 201

Sentiment analysis during Hurricane Sandy in emergency response

Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of users about different aspects of products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying such sentiments from online social networking sites can help emergency responders understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. In this paper, we perform a sentiment analysis of tweets posted on Twitter during the disastrous Hurricane Sandy and visualize online users' sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to their locations, but also based on the distance from the disaster. In addition, we study how the divergence of sentiments in a tweet posted during the hurricane affects the tweet retweetability. We find that extracting sentiments during a disaster may help emergency responders develop stronger situational awareness of the disaster zone itself

Konzept und Evaluation einer Facebook-Applikation zur crossmedialen Selbstorganisation freiwilliger Helfer

Das mitteleuropäische Hochwasser 2013 sorgte für große Schäden in weiten Teilen Deutschlands. Währenddessen und in der anschließenden Wiederherstellungsphase koordinierten betroffene und nicht betroffene Bürger ihre Hilfsaktivitäten nicht nur vor Ort, sondern auch in sozialen Medien wie Twitter, Facebook und mit Tools wie Google Maps. Basierend auf einer Vorstudie zu den Aktivitäten in Twitter und Facebook sowie Interviews mit „Digital Volunteers“ (hier: Gründer und Moderatoren von Facebook-Gruppen zum Hochwasser) stellt dieser Beitrag eine als Facebook-App realisierte crossmediale Applikation zur gruppen- und plattformübergreifenden Informationsbeschaffung und -Veröffentlichung vor, die der (Selbst-)Koordination ungebundener Helfer dienen soll. Diese wurde mit 20 Nutzern qualitativ evaluiert und zeigt Implikationen für die technische Unterstützung der Partizipation Freiwilliger in Katastrophenlagen auf

Konzept und Evaluation einer Facebook-Applikation zur crossmedialen Selbstorganisation freiwilliger Helfer

Das mitteleuropäische Hochwasser 2013 sorgte für große Schäden in weiten Teilen Deutschlands. Währenddessen und in der anschließenden Wiederherstellungsphase koordinierten betroffene und nicht betroffene Bürger ihre Hilfsaktivitäten nicht nur vor Ort, sondern auch in sozialen Medien wie Twitter, Facebook und mit Tools wie Google Maps. Basierend auf einer Vorstudie zu den Aktivitäten in Twitter und Facebook sowie Interviews mit „Digital Volunteers“ (hier: Gründer und Moderatoren von Facebook-Gruppen zum Hochwasser) stellt dieser Beitrag eine als Facebook-App realisierte crossmediale Applikation zur gruppen- und plattformübergreifenden Informationsbeschaffung und -Veröffentlichung vor, die der (Selbst-)Koordination ungebundener Helfer dienen soll. Diese wurde mit 20 Nutzern qualitativ evaluiert und zeigt Implikationen für die technische Unterstützung der Partizipation Freiwilliger in Katastrophenlagen auf

Beyond the Trustworthy Tweet: A Deeper Understanding of Microblogged Data Use by Disaster Response and Humanitarian Relief Organizations.”

ABSTRACT In this paper we present findings from interviews conducted with representatives from large international disaster response organizations concerning their use of social media data in crisis response. We present findings in which the barriers to use by responding organizations have gone beyond simple discussions of trustworthiness to that of more operational issues rather than mere data quality. We argue that the landscape of the use of microblogged data in crisis response is varied, with pockets of use and acceptance among organizations. We found that microblogged data is useful to responders in situations where information is limited, such as at the beginning of an emergency response effort, and when the risks of ignoring an accurate response outweigh the risks of acting on an incorrect one. In some situations, such as search and rescue operations, microblogged data may never meet the standards of quality required. In others, such as resource and supply management, microblogging data could be useful as long as it is appropriately verified and classified

Urban forecast: An analysis of a crowdsourced mobile app for crisis management

People around the world have become more connected thanks to the rise of social technology. As a result, that same technology has allowed us to witness the amount of violence and disastrous events that people around the world are experiencing. Civilians in Syria are constantly caught between rebel forces and the Syrian government\u27s army with no way of knowing where the next attack will be. People in Colorado had to wait for news updates on the wildfires of 2012 to make critical decisions on whether to evacuate or stay in their homes. A man in Mexico had all his personal belongings stolen at gunpoint when he came across a cartel-enforced blockade on his way to the grocery store. All these situations could have been avoided if those people had information about dangerous locations right away to help them make decisions. Civilians themselves who have just experienced the danger have valuable information that they can share to help other people avoid the same situation. This thesis presents a tool called Urban Forecast that can help citizens avoid dangerous locations and events by posting it on a map in the application and having it notify every other user around that area. Initial results suggest that Urban Forecast is effective at helping people avoid dangerous situations. Future designs based on results are also presented. The focus of this thesis is not entirely on the technology, but on the impact that it has on society in a hostile environment