scholarly journals Review article: Detection of actionable tweets in crisis events

2021 ◽  
Vol 21 (6) ◽  
pp. 1825-1845
Author(s):  
Anna Kruspe ◽  
Jens Kersten ◽  
Friederike Klan
Keyword(s):  
Social Media ◽  
Focal Point ◽  
Review Article ◽  
Data Sets ◽  
Social Media Data ◽  
Semantic Classification ◽  
Crisis Events ◽  
Media Data ◽  
Crisis Situations

Abstract. Messages on social media can be an important source of information during crisis situations. They can frequently provide details about developments much faster than traditional sources (e.g., official news) and can offer personal perspectives on events, such as opinions or specific needs. In the future, these messages can also serve to assess disaster risks. One challenge for utilizing social media in crisis situations is the reliable detection of relevant messages in a flood of data. Researchers have started to look into this problem in recent years, beginning with crowdsourced methods. Lately, approaches have shifted towards an automatic analysis of messages. A major stumbling block here is the question of exactly what messages are considered relevant or informative, as this is dependent on the specific usage scenario and the role of the user in this scenario. In this review article, we present methods for the automatic detection of crisis-related messages (tweets) on Twitter. We start by showing the varying definitions of importance and relevance relating to disasters, leading into the concept of use case-dependent actionability that has recently become more popular and is the focal point of the review paper. This is followed by an overview of existing crisis-related social media data sets for evaluation and training purposes. We then compare approaches for solving the detection problem based (1) on filtering by characteristics like keywords and location, (2) on crowdsourcing, and (3) on machine learning technique. We analyze their suitability and limitations of the approaches with regards to actionability. We then point out particular challenges, such as the linguistic issues concerning social media data. Finally, we suggest future avenues of research and show connections to related tasks, such as the subsequent semantic classification of tweets.

scholarly journals Review article: Detection of informative tweets in crisis events

2020 ◽  
Author(s):  
Anna Kruspe ◽  
Jens Kersten ◽  
Friederike Klan
Keyword(s):  
Social Media ◽  
Review Article ◽  
Machine Learning Techniques ◽  
Data Sets ◽  
Semantic Classification ◽  
Crisis Events ◽  
Learning Techniques ◽  
Media Data ◽  
Crisis Situations

Abstract. Messages on social media can be an important source of information during crisis situations, be they short-term disasters or longer-term events like COVID-19. They can frequently provide details about developments much faster than traditional sources (e.g. official news) and can offer personal perspectives on events, such as opinions or specific needs. In the future, these messages can also serve to assess disaster risks. One challenge for utilizing social media in crisis situations is the reliable detection of informative messages in a flood of data. Researchers have started to look into this problem in recent years, beginning with crowd-sourced methods. Lately, approaches have shifted towards an automatic analysis of messages. In this review article, we present methods for the automatic detection of crisis-related messages (tweets) on Twitter. We start by showing the varying definitions of importance and relevance relating to disasters, as they can serve very different purposes. This is followed by an overview of existing, crisis-related social media data sets for evaluation and training purposes. We then compare approaches for solving the detection problem based (1) on filtering by characteristics like keywords and location, (2) on crowdsourcing, and (3) on machine learning techniques with regard to their focus, their data requirements, their technical prerequisites, their efficiency and accuracy, and their time scales. These factors determine the suitability of the approaches for different expectations, but also their limitations. We identify which aspects each of them can contribute to the detection of informative tweets, and which areas can be improved upon in the future.We point out particular challenges, such as the linguistic issues concerning this kind of data. Finally, we suggest future avenues of research, and show connections to related tasks, such as the subsequent semantic classification of tweets.

scholarly journals What Your Tweets Tell Us About You: Identity, Ownership and Privacy of Twitter Data

2012 ◽  
Vol 7 (1) ◽  
pp. 174-197 ◽  
Author(s):  
Heather Small ◽  
Kristine Kasianovitz ◽  
Ronald Blanford ◽  
Ina Celaya
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Data Sets ◽  
Data Set ◽  
Social Media Data ◽  
Twitter Data ◽  
Other Information ◽  
Rich Data ◽  
Additional Value ◽  
Media Data

Social networking sites and other social media have enabled new forms of collaborative communication and participation for users, and created additional value as rich data sets for research. Research based on accessing, mining, and analyzing social media data has risen steadily over the last several years and is increasingly multidisciplinary; researchers from the social sciences, humanities, computer science and other domains have used social media data as the basis of their studies. The broad use of this form of data has implications for how curators address preservation, access and reuse for an audience with divergent disciplinary norms related to privacy, ownership, authenticity and reliability.In this paper, we explore how the characteristics of the Twitter platform, coupled with an ambiguous and evolving understanding of privacy in networked communication, and divergent disciplinary understandings of the resulting data, combine to create complex issues for curators trying to ensure broad-based and ethical reuse of Twitter data. We provide a case study of a specific data set to illustrate how data curators can engage with the topics and questions raised in the paper. While some initial suggestions are offered to librarians and other information professionals who are beginning to receive social media data from researchers, our larger goal is to stimulate discussion and prompt additional research on the curation and preservation of social media data.

Social Media-Based Data Collection and Analysis in Educational Research

2020 ◽  
pp. 54-77
Author(s):  
Liuli Huang
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Educational Research ◽  
Media In Education ◽  
Social Media Data ◽  
Educational Processes ◽  
Data Collection And Analysis ◽  
Media Data ◽  
Social Media In Education

The past decades have brought many changes to education, including the role of social media in education. Social media data offer educational researchers first-hand insights into educational processes. This is different from most traditional and often obtrusive data collection methods (e.g., interviews and surveys). Many researchers have explored the role of social media in education, such as the value of social media in the classroom, the relationship between academic achievement and social media. However, the role of social media in educational research, including data collection and analysis from social media, has been examined to a far lesser degree. This study seeks to discuss the potential of social media for educational research. The purpose of this chapter is to illustrate the process of collecting and analyzing social media data through a pilot study of current math educational conditions.

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 Success in an Online Giving Day: The Role of Social Media in Fundraising

2019 ◽  
Vol 49 (1) ◽  
pp. 74-92 ◽  
Author(s):  
Abhishek Bhati ◽  
Diarmuid McDonnell
Keyword(s):  
Social Media ◽  
Organizational Factors ◽  
Network Size ◽  
Audience Engagement ◽  
Social Media Data ◽  
Size Number ◽  
Social Media Platforms ◽  
The Relationship ◽  
Media Data

Social media platforms offer nonprofits considerable potential for crafting, supporting, and executing successful fundraising campaigns. How impactful are attempts by these organizations to utilize social media to support fundraising activities associated with online Giving Days? We address this question by testing a number of hypotheses of the effectiveness of using Facebook for fundraising purposes by all 704 nonprofits participating in Omaha Gives 2015. Using linked administrative and social media data, we find that fundraising success—as measured by the number of donors and value of donations—is positively associated with a nonprofit’s Facebook network size (number of likes), activity (number of posts), and audience engagement (number of shares), as well as net effects of organizational factors including budget size, age, and program service area. These results provide important new empirical insights into the relationship between social media utilization and fundraising success of nonprofits.

Information Visualizations as a Tool to Study Users’ Social Media Privacy Concerns

2018 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Jenna Jacobson ◽  
Elizabeth Dubois
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Job Applicants ◽  
Social Media Data ◽  
Privacy Concerns ◽  
Comfort Levels ◽  
People’S Attitudes ◽  
Media Data ◽  
Information Visualizations

The amount and complexity of data that can be accessed from social media has been increasing exponentially. We examine the value of using information visualizations as a tool to study people’s attitudes and perceptions regarding their social media data being used by third parties. In the context of using social media to screen job applicants, we investigate the role of visualizations in studying users’ social media privacy concerns. Utilizing an online survey of 454 participants, we compare participants’ comfort levels in relation to different types of publicly accessible social media data. The results partially support the supposition that analytical information based on some form of data analysis will receive a stronger reaction when accompanied by representative visualizations.

Harnessing social media to understand tourist mobility: the role of information technology and big data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jinyan Chen ◽  
Susanne Becken ◽  
Bela Stantic
Keyword(s):  
Social Media ◽  
Literature Review ◽  
Current Trend ◽  
Social Media Data ◽  
Content Type ◽  
Use Of Data ◽  
Social Media Platforms ◽  
The City ◽  
Media Data

Purpose This paper aims to examine key parameters of scholarly context and geographic focus and provide an assessment of theoretical underpinnings of studies in the field of social media and visitor mobility. This review also summarised the characteristics of social media data, including how data are collected from different social media platforms and their advantages and limitations. The stocktake of research in this field was completed by examining technologies and applied methods that supported different research questions. Design/methodology/approach This literature review applied a mix of methods to conduct a literature review. This review analysed 82 journal articles on using social media to track visitors’ movements between 2014 and November 2020. The literature compared the different social media, discussed current applied theories, available technologies, analysed the current trend and provided advice for future directions. Findings This review provides a state-of-the-art assessment of the research to date on tourist mobility analysed using social media data. The diversity of scales (with a dominant focus on the city-scale), platforms and methods highlight that this field is emerging, but it also reflects the complexity of the tourism phenomenon. This review identified a lack of theory in this field, and it points to ongoing challenges in ensuring appropriate use of data (e.g. differentiating travellers from residents) and the ethics surrounding them. Originality/value The findings guide researchers, especially those with no computer science background, on the different types of approaches, data sources and methods available for tracking tourist mobility by harnessing social media. Depending on the particular research interest, different tools for processing and visualization are available.

scholarly journals The role of social media data in operations and production management

2015 ◽  
Vol 55 (17) ◽  
pp. 5027-5036 ◽  
Author(s):  
Hing Kai Chan ◽  
Ewelina Lacka ◽  
Rachel W.Y. Yee ◽  
Ming K. Lim
Keyword(s):  
Social Media ◽  
Production Management ◽  
Social Media Data ◽  
Media Data
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