Processing Social Media Data for Crisis Management in Athena

2015 ◽  
pp. 3-14
Author(s):  
Babak Akhgar ◽  
Helen Gibson
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Social Media Data ◽  
Media Data

A Sentiment Analysis and Role of Twitter for Health Communications

2022 ◽  
pp. 188-205
Author(s):  
Erkan Çiçek ◽  
Uğur Gündüz
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Semantic Analysis ◽  
Social Media Data ◽  
Global Pandemic ◽  
The Difference ◽  
Textual Content ◽  
The Impact ◽  
Media Data

Social media has been in our lives so much lately that it is an undeniable fact that global pandemics, which constitute an important part of our lives, are also affected by these networks and that they exist in these networks and share the users. The purpose of making this hashtag analysis is to reveal the difference in discourse and language while analyzing Twitter data and to evaluate the effects of a global pandemic crisis on language, message, and crisis management with social media data. This form of analysis is typically completed through amassing textual content data then investigating the “sentiment” conveyed. Within the scope of the study, 11,300 Twitter messages posted with the #stayhome hashtag between 30 May 2020 and 6 June 2020 were examined. The impact and reliability of social media in disaster management could be questioned by carrying out a content analysis based totally on the semantic analysis of the messages given on the Twitter posts with the phrases and frequencies used.

scholarly journals Big Data in a Crisis? Creating Social Media Datasets for Crisis Management Research

i-com ◽  
2016 ◽  
Vol 15 (3) ◽  
Author(s):  
Christian Reuter ◽  
Thomas Ludwig ◽  
Christoph Kotthaus ◽  
Marc-André Kaufhold ◽  
Elmar von Radziewski ◽  
...  
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Emergency Services ◽  
Data Sets ◽  
Management Research ◽  
Social Media Data ◽  
Public Data ◽  
Ease Of Access ◽  
Use Of Social Media ◽  
Media Data

AbstractA growing body of research in the area of information systems for crisis management is based on data from social media. After almost every larger disaster studies emerge with the focus on the specific use of social media. Much of this research is based on Twitter data, due to the ease of access of this (mainly public) data, compared to (more closed) data, such as Facebook or Google+. Based on the experience gained from a research project on social media in emergencies and our task to collect social media data sets for other partners, we present the design and evaluation of a graphical user interface that supports those stakeholders (such as emergency services or researchers) that are interested in creating social media datasets for further crisis management research. We do not specifically focus on the analysis of social media data. Rather we aim to support the gathering process and how actors without sophisticated technical skills can be supported to get what they want and especially need: relevant social media data. Within this article, we present a practice-oriented approach and implications for designing tools that support the collection of social media data as well as future work.

scholarly journals Batch-based active learning: Application to social media data for crisis management

2018 ◽  
Vol 93 ◽  
pp. 232-244 ◽  
Author(s):  
Daniela Pohl ◽  
Abdelhamid Bouchachia ◽  
Hermann Hellwagner
Keyword(s):  
Social Media ◽  
Active Learning ◽  
Crisis Management ◽  
Social Media Data ◽  
Media Data

Smart De-Identification of Social Media Data

2014 ◽  
Author(s):  
Kathleen M. Carley ◽  
L. R. Carley ◽  
Jonathan Storrick
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Media Data

Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives (Preprint)

2018 ◽  
Author(s):  
Anika Oellrich ◽  
George Gkotsis ◽  
Richard James Butler Dobson ◽  
Tim JP Hubbard ◽  
Rina Dutta
Keyword(s):  
Social Media ◽  
Family Relationships ◽  
Text Processing ◽  
Automated Analysis ◽  
Health Concern ◽  
Dementia Diagnosis ◽  
Data Set ◽  
Social Media Data ◽  
Real Time Processing ◽  
Media Data

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.

Citizens, Elites, and Social Media Methodological Challenges and Opportunities in the Study of Persuasion and Mobilization

2019 ◽  
pp. 1036-1058
Author(s):  
Philip Habel ◽  
Yannis Theocharis
Keyword(s):  
Social Media ◽  
Big Data ◽  
Supply And Demand ◽  
Political Process ◽  
The Political ◽  
The Novel ◽  
Complete Understanding ◽  
Social Media Data ◽  
Challenges And Opportunities ◽  
Media Data

In the last decade, big data, and social media in particular, have seen increased popularity among citizens, organizations, politicians, and other elites—which in turn has created new and promising avenues for scholars studying long-standing questions of communication flows and influence. Studies of social media play a prominent role in our evolving understanding of the supply and demand sides of the political process, including the novel strategies adopted by elites to persuade and mobilize publics, as well as the ways in which citizens react, interact with elites and others, and utilize platforms to persuade audiences. While recognizing some challenges, this chapter speaks to the myriad of opportunities that social media data afford for evaluating questions of mobilization and persuasion, ultimately bringing us closer to a more complete understanding Lasswell’s (1948) famous maxim: “who, says what, in which channel, to whom, [and] with what effect.”

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