Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection

Research using online datasets from social media platforms continues to grow in prominence, but recent research suggests that platform users are sometimes uncomfortable with the ways their posts and content are used in research studies. While previous research has suggested that a variety of contextual variables may influence this discomfort, such factors have yet to be isolated and compared. In this article, we present results from a factorial vignette survey of American Facebook users. Findings reveal that researcher domain, content type, purpose of data use, and awareness of data collection all impact respondents’ comfort—measured via judgments of acceptability and concern—with diverse data uses. We provide guidance to researchers and ethics review boards about the ways that user reactions to research uses of their data can serve as a cue for identifying sensitive data types and uses.

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Social Media-Based Data Collection and Analysis in Educational Research

Advancing Educational Research With Emerging Technology - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-7998-1173-2.ch004 ◽

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.

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Attitudes and Knowledge of Adolescents in Jordan Regarding the Ethics of Social Media Data Use for Research Purposes

Journal of Empirical Research on Human Research Ethics ◽

10.1177/1556264620901390 ◽

2020 ◽

Vol 15 (1-2) ◽

pp. 87-96

Author(s):

Hiba Wazeer Al Zou’bi ◽

Moawiah Khatatbeh ◽

Karem H. Alzoubi ◽

Omar F. Khabour ◽

Wael K. Al-Delaimy

Keyword(s):

Social Media ◽

Informed Consent ◽

Online Survey ◽

Personal Information ◽

Data Use ◽

Ethical Aspects ◽

Social Media Data ◽

Attitudes And Knowledge ◽

Media Data ◽

Research Studies

This study assessed the awareness and attitudes of adolescents in Jordan concerning the ethics of using their social media data for scientific studies. Using an online survey, 393 adolescents were recruited (mean age: 17.2 years ± 1.8). The results showed that 88% of participants were using their real personal information on social media sites, with males more likely to provide their information than females. More than two thirds of participants (72.5%) were aware that researchers may use their data for research purposes, with the majority believing that informed consent must be obtained from both the adolescents and their parents. However, more than three quarters of those surveyed (76%) did not trust the results of research that depended on collecting data from social media. These findings suggest that adolescents in Jordan understood most of the ethical aspects related to the utilization of their data from social media websites for research studies.

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Social Media Intelligence and Learning Environment: an Open Source Framework for Social Media Data Collection, Analysis and Curation

2019 15th International Conference on eScience (eScience) ◽

10.1109/escience.2019.00035 ◽

2019 ◽

Author(s):

Chen Wang ◽

Luigi Marini ◽

Chieh-Li Chin ◽

Nickolas Vance ◽

Curtis Donelson ◽

...

Keyword(s):

Social Media ◽

Data Collection ◽

Learning Environment ◽

Open Source ◽

Social Media Data ◽

Open Source Framework ◽

Media Data ◽

Social Media Intelligence

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DRENAJ: Distributed social media data collection system

2015 23nd Signal Processing and Communications Applications Conference (SIU) ◽

10.1109/siu.2015.7130351 ◽

2015 ◽

Author(s):

Onur Gungor ◽

Suzan Uskudarli ◽

A. Taylan Cemgil

Keyword(s):

Social Media ◽

Data Collection ◽

Collection System ◽

Social Media Data ◽

Data Collection System ◽

Media Data

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Mining social media data: How are research sponsors and researchers addressing the ethical challenges?

Research Ethics ◽

10.1177/1747016117738559 ◽

2017 ◽

Vol 14 (2) ◽

pp. 1-39 ◽

Cited By ~ 16

Author(s):

Joanna Taylor ◽

Claudia Pagliari

Keyword(s):

Social Media ◽

Health Research ◽

Social Research ◽

International Association ◽

Academic Community ◽

Ethical Challenges ◽

Ethical Considerations ◽

Social Media Data ◽

Ethics Guidelines ◽

Media Data

Background: Data representing people’s behaviour, attitudes, feelings and relationships are increasingly being harvested from social media platforms and re-used for research purposes. This can be ethically problematic, even where such data exist in the public domain. We set out to explore how the academic community is addressing these challenges by analysing a national corpus of research ethics guidelines and published studies in one interdisciplinary research area. Methods: Ethics guidelines published by Research Councils UK (RCUK), its seven-member councils and guidelines cited within these were reviewed. Guidelines referring to social media were classified according to published typologies of social media research uses and ethical considerations for social media mining. Using health research as an exemplar, PubMed was searched to identify studies using social media data, which were assessed according to their coverage of ethical considerations and guidelines. Results: Of the 13 guidelines published or recommended by RCUK, only those from the Economic and Social Research Council, the British Psychological Society, the International Association of Internet Researchers and the National Institute for Health Research explicitly mentioned the use of social media. Regarding data re-use, all four mentioned privacy issues but varied with respect to other ethical considerations. The PubMed search revealed 156 health-related studies involving social media data, only 50 of which mentioned ethical concepts, in most cases simply stating that they had obtained ethical approval or that no consent was required. Of the nine studies originating from UK institutions, only two referred to RCUK ethics guidelines or guidelines cited within these. Conclusions: Our findings point to a deficit in ethical guidance for research involving data extracted from social media. Given the growth of studies using these new forms of data, there is a pressing need to raise awareness of their ethical challenges and provide actionable recommendations for ethical research practice.

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Sentiment Analysis of Tweets for Estimating Criticality and Security of Events

Improving the Safety and Efficiency of Emergency Services ◽

10.4018/978-1-7998-2535-7.ch013 ◽

2020 ◽

pp. 293-319 ◽

Cited By ~ 1

Author(s):

V. Subramaniyaswamy ◽

R. Logesh ◽

M. Abejith ◽

Sunil Umasankar ◽

A. Umamakeswari

Keyword(s):

Social Media ◽

Data Collection ◽

Sentiment Analysis ◽

Quantitative Result ◽

Law Enforcement Agencies ◽

Social Media Data ◽

Software Application ◽

The World ◽

Media Data ◽

Different Levels

Social Media has become one of the major industries in the world. It has been noted that almost three fourth of the world's population use social media. This has instigated many researches towards social media. One such useful application is the sentimental analysis of real time social media data for security purposes. The insights that are generated can be used by law enforcement agencies and for intelligence purposes. There are many types of analyses that have been done for security purposes. Here, the authors propose a comprehensive software application which will meticulously scrape data from Twitter and analyse them using the lexicon based analysis to look for possible threats. They propose a methodology to obtain a quantitative result called criticality to assess the level of threat for a public event. The results can be used to understand people's opinions and comments with regard to specific events. The proposed system combines this lexicon based sentimental analysis along with deep data collection and segregates the emotions into different levels to analyse the threat for an event.

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