OntoDSumm : Ontology based Tweet Summarization for Disaster Events

The huge popularity of social media platforms like Twitter attracts a large fraction of users to share real-time information and short situational messages during disasters. A summary of these tweets is required by the government organizations, agencies, and volunteers for efficient and quick disaster response. However, the huge influx of tweets makes it difficult to manually get a precise overview of ongoing events. To handle this challenge, several tweet summarization approaches have been proposed. In most of the existing literature, tweet summarization is broken into a two-step process where in the first step, it categorizes tweets, and in the second step, it chooses representative tweets from each category. There are both supervised as well as unsupervised approaches found in literature to solve the problem of first step. Supervised approaches requires huge amount of labelled data which incurs cost as well as time. On the other hand, unsupervised approaches could not clusters tweet properly due to the overlapping keywords, vocabulary size, lack of understanding of semantic meaning etc. While, for the second step of summarization, existing approaches applied different ranking methods where those ranking methods are very generic which fail to compute proper importance of a tweet respect to a disaster. Both the problems can be handled far better with proper domain knowledge. In this paper, we exploited already existing domain knowledge by the means of ontology in both the steps and proposed a novel disaster summarization method OntoDSumm. We evaluate this proposed method with 4 state-of-the-art methods using 10 disaster datasets. Evaluation results reveal that OntoDSumm outperforms existing methods by approximately 2-66% in terms of ROUGE-1 F1 score

Can we predict a riot? Disruptive event detection using Twitter

In recent years, there has been increased interest in real-world event detection using publicly accessible data made available through Internet technology such as Twitter, Facebook, and YouTube. In these highly interactive systems, the general public are able to post real-time reactions to “real world” events, thereby acting as social sensors of terrestrial activity. Automatically detecting and categorizing events, particularly small-scale incidents, using streamed data is a non-trivial task but would be of high value to public safety organisations such as local police, who need to respond accordingly. To address this challenge, we present an end-to-end integrated event detection framework that comprises five main components: data collection, pre-processing, classification, online clustering, and summarization. The integration between classification and clustering enables events to be detected, as well as related smaller-scale “disruptive events,” smaller incidents that threaten social safety and security or could disrupt social order. We present an evaluation of the effectiveness of detecting events using a variety of features derived from Twitter posts, namely temporal, spatial, and textual content. We evaluate our framework on a large-scale, real-world dataset from Twitter. Furthermore, we apply our event detection system to a large corpus of tweets posted during the August 2011 riots in England. We use ground-truth data based on intelligence gathered by the London Metropolitan Police Service, which provides a record of actual terrestrial events and incidents during the riots, and show that our system can perform as well as terrestrial sources, and even better in some cases

Over-indebtedness and the interplay of factual and mental money management: An interview study

Previous research has shown that money management contributes to over-indebtedness. This article sheds new light on this relation by looking at factual money management and its mental underpinnings, mental accounting. In a conceptual model we propose that fuzzy factual and mental money management practices aggravated by lack of congruency between factual and mental structures play an important role in over-indebtedness. Twenty-five in-depth interviews deliver preliminary support for this proposition. Successful financial control seems to build on efficient and inter-coordinated factual and mental money management. This reduces the willpower necessary for controlling financial behavior and helps to prevent and fight over-indebtedness.debt, money management, mental accounting, self-control

PORTRAIT: a hybrid aPproach tO cReate extractive ground-TRuth summAry for dIsaster evenT

Disaster summarization approaches provide an overview of the important information posted during disaster events on social media platforms, such as, Twitter. However, the type of information posted significantly varies across disasters depending on several factors like the location, type, severity, etc. Verification of the effectiveness of disaster summarization approaches still suffer due to the lack of availability of good spectrum of datasets along with the ground-truth summary. Existing approaches for ground-truth summary generation (ground-truth for extractive summarization) relies on the wisdom and intuition of the annotators. Annotators are provided with a complete set of input tweets from which a subset of tweets is selected by the annotators for the summary. This process requires immense human effort and significant time. Additionally, this intuition-based selection of the tweets might lead to a high variance in summaries generated across annotators. Therefore, to handle these challenges, we propose a hybrid (semi-automated) approach (PORTRAIT) where we partly automate the ground-truth summary generation procedure. This approach reduces the effort and time of the annotators while ensuring the quality of the created ground-truth summary. We validate the effectiveness of PORTRAIT on 5 disaster events through quantitative and qualitative comparisons of ground-truth summaries generated by existing intuitive approaches, a semi-automated approach, and PORTRAIT. We prepare and release the ground-truth summaries for 5 disaster events which consist of both natural and man-made disaster events belonging to 4 different countries. Finally, we provide a study about the performance of various state-of-the-art summarization approaches on the ground-truth summaries generated by PORTRAIT using ROUGE-N F1-scores

@Houstonpolice: an exploratory case of Twitter during Hurricane Harvey

Abstract Purpose The purpose of this paper is to examine the Houston Police Department (HPD)’s public engagement efforts using Twitter during Hurricane Harvey, which was a large-scale urban crisis event. Design/methodology/approach This study harvested a corpus of over 13,000 tweets using Twitter’s streaming API, across three phases of the Hurricane Harvey event: preparedness, response and recovery. Both text and social network analysis (SNA) techniques were employed including word clouds, n-gram analysis and eigenvector centrality to analyze data. Findings Findings indicate that departmental tweets coalesced around topics of protocol, reassurance and community resilience. Twitter accounts of governmental agencies, such as regional police departments, local fire departments, municipal offices, and the personal accounts of city’s police and fire chiefs were the most influential actors during the period under review, and Twitter was leveraged as de facto a 9-1-1 dispatch. Practical implications Emergency management agencies should consider adopting a three-phase strategy to improve communication and narrowcast specific types of information corresponding to relevant periods of a crisis episode. Originality/value Previous studies on police agencies and social media have largely overlooked discrete periods, or phases, in crisis events. To address this gap, the current study leveraged text and SNA to investigate Twitter communications between HPD and the public. This analysis advances understanding of information flows on law enforcement social media networks during crisis and emergency events

Analyzing Twitter Feeds to Facilitate Crises Informatics and Disaster Response During Mass Emergencies

It is a common practice these days for general public to use various micro-blogging platforms, predominantly Twitter, to share ideas, opinions and information about things and life. Twitter is also being increasingly used as a popular source of information sharing during natural disasters and mass emergencies to update and communicate the extent of the geographic phenomena, report the affected population and casualties, request or provide volunteering services and to share the status of disaster recovery process initiated by humanitarian-aid and disaster-management organizations. Recent research in this area has affirmed the potential use of such social media data for various disaster response tasks. Even though the availability of social media data is massive, open and free, there is a significant limitation in making sense of this data because of its high volume, variety, velocity, value, variability and veracity. The current work provides a comprehensive framework of text processing and analysis performed on several thousands of tweets shared on Twitter during natural disaster events. Specifically, this work em- ploys state-of-the-art machine learning techniques from natural language processing on tweet content to process the ginormous data generated at the time of disasters. This study shall serve as a basis to provide useful actionable information to the crises management and mitigation teams in planning and preparation of effective disaster response and to facilitate the development of future automated systems for handling crises situations

Global Citizens in the 21st-Century Classroom: A Mixed-Methods Study of Motivational Aspects of Global Awareness

The present global setting is increasingly driven by the interdependence of heightened environmental, political, socio-economic, and technological forces. As a result, today’s students need a variety of skills to succeed on both professional and personal levels. A wide and increasing array of scholars strongly advocates for students to achieve enhanced global awareness to become global citizens and to successfully navigate this challenging global environment. The growing importance of global awareness and understanding students’ motivational behaviors toward its attainment strongly inspired the purpose of this dissertation study. A convergent parallel mixed-methods design was utilized for this dissertation study to examine how an ethnically, racially, and socio-economically diverse group of high school students (n = 172) reported their motivational characteristics associated with their global awareness levels as a result of participating in a global-themed curriculum program. Data collection and analyses were grounded in Self-Determination Theory (Ryan & Deci, 2000), which includes intrinsic and varied extrinsic nuances and descriptions of the respective roles of these forms of motivation in cognitive and social development. As a means to assess the participating students’ levels of motivation and global awareness, an electronic survey was administered, including the following measures: (a) the Situational Motivational Scale (SIMS) (Guay, Vallerand, & Blanchard, 2000), (b) the Programme for International Student Assessment – Global Competence Student Information Questionnaire (PISA; Organization for Economic Cooperation and Development, 2018), and (c) a demographic questionnaire. The student sample’s quantitative data were obtained from this online survey instrument. The qualitative data were taken from focus group discussions, during which students (n = 23) reflected on various motivators for their enrollments and participations in their respective global-themed courses. Based on the quantitative data analyses, the student sample possessed motivational characteristics to participate in their respective global-themed courses, as highlighted in the SIMS’ Intrinsic Motivation and Identified Regulation subscales scores. In addition, the respective data scores for several PISA subscales, namely, Awareness of Global Issues, Student’s Engagement with Others, Re: Global Issues, Interest in Learning About Other Cultures, and Global Competence Activities at School, revealed the strongest tendency toward measurements of the students’ global awareness. Moreover, various correlation and multiple regression analyses of the independent and dependent quantitative data variables showed evidence of the student sample’s global awareness. The qualitative data analysis revealed various interrelated factors that led to the development of the students’ global awareness and the many perceived benefits they had received from participating in those courses, including improved academic skills and heightened global perspectives that led to the development of enhanced empathy and desires to become social cause advocates. The integrated data analyses revealed that the SIMS Intrinsic Motivation and Identified Regulation subscales data related to students’ participations in the global-themed courses were supported by the qualitative results anchored in motivations to seek more in-depth knowledge about global studies, and to participate in higher-level curricula to earn college credits. Components of the highest-scoring PISA subscales, such as the ability to discuss and to analyze topical global issues like the global climate crisis and the technological revolution, and keeping abreast of newsworthy global events via social media platforms, which indicated important elements of global awareness, were clearly supported in the qualitative data. The findings of this study reinforced the necessity for students to become better prepared to face the numerous challenges within an increasingly interconnected and competitive working world. This dissertation has important implications for researchers in the field of educational psychology and educators engaged in the creation and delivery of 21st-century skills and global awareness-inspired curricula. The following are recommendations to include opportunities for developing global awareness: (a) create learning environments to foster innate psychological personal needs such as competency, autonomy, and relatedness (Deci & Ryan, 2000); (b) promote foreign language learning, including realistic experiences to reinforce the numerous benefits of that important skill; and, (c) embrace empathy and tolerance toward others, leading to demonstrated needs for social cause advocacy as important extensions of global awareness development