[Cfp] Fwd: [AISWorld] CFP IJISCRAM 8(3)

-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP IJISCRAM 8(3) Datum: Fri, 5 May 2017 00:10:05 -0700 Von: Murray Jennex mjennex@mail.sdsu.edu An: aisworld@lists.aisnet.org

Abstract Announcement for International Journal of Information Systems for Crisis Response and Management (IJISCRAM) 8(3)The contents of the latest issue of: *International Journal of Information Systems for Crisis Response and Management (IJISCRAM)* *An Official Publication of the ISCRAM Association http://www.iscram.org/category-membership/* Volume 8, Issue 3, July - September 2016 Indexed by: INSPEC Published: Quarterly in Print and Electronically ISSN: 1937-9390; EISSN: 1937-9420; Published by IGI Global Publishing, Hershey, USA www.igi-global.com/ijiscram http://www.igi-global.com/journal/international-journal-information-systems-crisis/1119

Editor-in-Chief: Víctor Amadeo Bañuls Silvera (Universidad Pablo de Olavide, Spain) and Murray E. Jennex (San Diego State University, USA) *Note: The International Journal of Information Systems for Crisis Response and Management (IJISCRAM) has an Open Access option, which allows individuals and institutions unrestricted access to its published content. Unlike traditional subscription-based publishing models, open access content is available without having to purchase or subscribe to the journal in which the content is published. All IGI Global manuscripts are accepted based on a double-blind peer review editorial process.*

*GUEST EDITORIAL PREFACE*

Special Issue on Contextual Data for Crisis Management and Response

Andrea H. Tapia (School of IS and Technology, Penn State University, University Park, PA, USA), Kathleen A. Moore (Mercyhurst University, Erie, PA, USA)

To obtain a copy of the Guest Editorial Preface, click on the link below. www.igi-global.com/pdf.aspx?tid=180300&ptid=131788&ctid=15&t=Special Issue on Contextual Data for Crisis Management and Response http://www.igi-global.com/pdf.aspx?tid=180300&ptid=131788&ctid=15&t=Special%20Issue%20on%20Contextual%20Data%20for%20Crisis%20Management%20and%20Response

*ARTICLE 1*

Enabling Rapid Classification of Social Media Communications During Crises

Muhammad Imran (Qatar Computing Research Institute, Doha, Qatar), Prasenjit Mitra (The Pennsylvania State University, University Park, PA, USA), Jaideep Srivastava (Qatar Computing Research Institute, Doha, Qatar)

The use of social media platforms such as Twitter by affected people during crises is considered a vital source of information for crisis response. However, rapid crisis response requires real-time analysis of online information. When a disaster happens, among other data processing techniques, supervised machine learning can help classify online information in real-time. However, scarcity of labeled data causes poor performance in machine training. Often labeled data from past event is available. Can past labeled data be reused to train classifiers? We study the usefulness of labeled data of past events. We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. Moreover, we propose two approaches (target labeling and active learning) to boost classification performance of a learning scheme. We perform extensive experimentation on real crisis datasets and show the utility of past-labeled data to train machine learning classifiers to process sudden-onset crisis-related data in real-time.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/enabling-rapid-classification-of-social-media-communications-during-crises/180301

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=180301

*ARTICLE 2*

Improving the Utility of Social Media Data to Emergency Responders through Emotional Content Detection

Shane Halse (Pennsylvania State University, University Park, PA, USA), Andrea H Tapia (Pennsylvania State University, University Park, PA, USA)

In the following paper, we will present an alternate method for the detection of emotional content within social media data. Current research has presented the traditional bag-of-words method in which a predefined corpus is used to measure the emotional context of each word within a message. Here we present a method in which a small subset of the data is labeled to generate a corpus which is then used to detect emotional content within the data. This research is being conducted on the dataset from hurricane Sandy in 2012. Our findings show an improvement upon the bag-of-words method. These findings would further the current research in improving the utilization of social media data within crisis response. In doing this we allow the average citizen to provide beneficial data to those in decision making roles.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/improving-the-utility-of-social-media-data-to-emergency-responders-through-emotional-content-detection/180302

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=180302

*ARTICLE 3*

Predicting Tweet Retweetability during Hurricane Disasters

Venkata Kishore Neppalli (University of North Texas, Computer Science and Engineering, Denton, TX, USA), Cornelia Caragea (University of North Texas, Computer Science and Engineering, Denton, TX, USA), Doina Caragea (Kansas State University, Department of Computer Science, Manhattan, KS, USA), Murilo Cerqueira Medeiros (University of North Texas, Computer Science and Engineering, Denton, TX, USA), Andrea H Tapia (Pennsylvania State University, University Park, PA, USA), Shane E. Halse (Pennsylvania State University, University Park, PA, USA)

Twitter is a vital source for obtaining information, especially during events such as natural disasters. Users can spread information on Twitter either by crafting new posts, which are called “tweets,” or by using the retweet mechanism to re-post previously created tweets. During natural disasters, identifying how likely a tweet is to be retweeted is crucial since it can help promote the spread of useful information in a social network such as Twitter, as well as it can help stop the spread of misinformation when corroborated with approaches that identify rumors and misinformation. In this paper, we present an analysis of retweeted tweets from two different hurricane disasters, to identify factors that affect retweetability. We then use these factors to extract features from tweets' content and user account information in order to develop models that automatically predict the retweetability of a tweet. The results of our experiments on Sandy and Patricia Hurricanes show the effectiveness of our features.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/predicting-tweet-retweetability-during-hurricane-disasters/180303

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=180303

*ARTICLE 4*

Mapping of Areas Presenting Specific Risks to Firefighters Due to Buried Technical Networks

Amélie Grangeat (French Alternative Energies and Atomic Energy Commission (CEA), Gramat, France), Stéphane Raclot (Brigade de Sapeurs Pompiers de Paris (BSPP), Paris, France), Floriane Brill (Brigade de Sapeurs Pompiers de Paris (BSPP), Paris, France), Emmanuel Lapebie (French Alternative Energies and Atomic Energy Commission (CEA), Gramat, France)

Vehicles or freight cars on fire below a bridge or inside a tunnel are exceptional events and imply difficult intervention conditions for firefighters. A buried technical network like high voltage electricity line, gas or steam pipeline around such a fire causes additional specifics risks. Vulnerability areas for firefighters are zones where both factors exist: a difficult incident area together with a specific risk like buried networks. They require intervention teams with specific emergency response capabilities. The paper proposes a method developed for the Paris Fire Brigade for vulnerability mapping. Results aim at improving the mobilization in allocating directly the specific responses capabilities intervention teams. Results are debated from an operational point of view. Cutting off several network lines during firefighters' interventions may strongly affect the society. In case of simultaneous incidents in vulnerable areas, firefighters could be an early warning system and inform authorities of the risk of services disruption.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/mapping-of-areas-presenting-specific-risks-to-firefighters-due-to-buried-technical-networks/180304

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=180304

------------------------------ For full copies of the above articles, check for this issue of the *International Journal of Information Systems for Crisis Response and Management (IJISCRAM)* in your institution's library. This journal is also included in the IGI Global aggregated *"InfoSci-Journals"* database: www.igi-global.com/isj http://www.igi-global.com/e-resources/infosci-databases/infosci-journals/. ------------------------------

*CALL FOR PAPERS*

Mission of IJISCRAM:

The mission of the *International Journal of Information Systems for Crisis Response and Management (IJISCRAM)* is to provide an outlet for innovative research in the area of information systems for crisis response and management. Research is expected to be rigorous but can utilize any accepted methodology and may be qualitative or quantitative in nature. The journal will provide a comprehensive cross disciplinary forum for advancing the understanding of the organizational, technical, human, and cognitive issues associated with the use of information systems in responding and managing crises of all kinds. The goal of the journal is to publish high quality empirical and theoretical research covering all aspects of information systems for crisis response and management. Full-length research manuscripts, insightful research and practice notes, and case studies will be considered for publication.

Indices of IJISCRAM:

- ACM Digital Library - Bacon's Media Directory - Cabell's Directories - DBLP - GetCited - Google Scholar - INSPEC - JournalTOCs - MediaFinder - Norwegian Social Science Data Services (NSD) - The Index of Information Systems Journals - The Standard Periodical Directory - Ulrich's Periodicals Directory

Coverage of IJISCRAM:

This journal covers all aspects of the crisis management information systems discipline, from organizational or social issues to technology support to decision making and knowledge representation. High quality submissions are encouraged using any qualitative or quantitative research methodology, focusing on the design, development, implementation, uses and evaluation of such systems. Submissions are especially encouraged covering the following topics in this discipline:

- Case studies, research methods, and modeling approaches - Collaborative and intelligent systems - Command and control - Communication technologies - Crisis planning, training, exercising, and gaming - Data fusion, representation, and visualization - Decision making and judgment - Disaster risk reduction, risk management, ad-hoc, and sensor networks - Early warning systems - Emergency response systems - Geographical information systems - Globalization and development issues - Healthcare and health information systems - Human-computer interaction - Humanitarian operations - Information systems strategy - Knowledge management and systems - Systems interoperability information systems infrastructures - Virtual teams and organizations

Interested authors should consult the journal's manuscript submission guidelines www.igi-global.com/calls-for-papers/international-journal-information-systems-crisis/1119 _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org