SMAGA

2019 ◽  
Vol 11 (2) ◽  
pp. 12-34
Author(s):  
Yuan Xue ◽  
Yilu Zhou
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Cultural Studies ◽  
Social Science ◽  
Cultural Study ◽  
Cross Cultural ◽  
Social Media Data ◽  
Cross Cultural Study ◽  
Media Data ◽  
Cross Cultural Studies

The study of national culture and cultural differences has immense value in today's business world. However, contemporary cross-cultural study instruments are subjective to many biases and intensive in terms of human labor. On the other hand, social media data offers tremendous opportunities for cross-cultural studies. However, it cannot be used directly as input for existing cross-cultural study applications in social science for being unstructured and noisy. In this work, the authors develop a text mining application called Social Media Associative Group Analysis (SMAGA). It effectively discovers information relevant to cultural values from social media data and represent such information using AGA verbal associations tuples. Experimental results show that the SMAGA framework can generate meaningful results in support of cross-cultural studies with much higher efficiency than traditional cross-cultural study instruments. This research underlines the emerging trend of developing text mining applications to automate cross-cultural and other types of social science studies.

Using social media data in diabetes care: Bridging the conceptual gap between health providers and patients (Preprint)

2021 ◽  
Author(s):  
Ru-Hsueh Wang ◽  
Yu-Wen Hong ◽  
Chia-Chun Li ◽  
Siao-Ling Li ◽  
Jenn-Long Liu ◽  
...  
Keyword(s):  
Social Media ◽  
Chinese Medicine ◽  
Sexual Dysfunction ◽  
Text Mining ◽  
Real World ◽  
Diabetes Care ◽  
Weight Reduction ◽  
Health Providers ◽  
Social Media Data ◽  
Media Data

BACKGROUND Diabetic patients with poor education about the disease may exhibit poor compliance and thus subsequently experience more complications. However, the conceptual gap between the diabetes education provided by health providers and the non-compliance of patients is still not well understood in the real world. OBJECTIVE Disclosing what people think about diabetes on social media may help to close this gap. METHODS In this study, social media data was collected from the OpView social media platform. After checking the quality of the data, we analyzed the trends in people’s discussions on the Internet using text mining. The natural language process, including word segmentation, and word count, and counting the relationships between the words. A word cloud is developed, and a clustering analyses are also performed. RESULTS There were 19,565 posts about diabetes collected from forums, community websites, and Q&A websites in 2017. The three most popular aspects of diabetes were diet (33.2%), life adjustment (21.2%), and avoiding complications (15.6%). Most of the discussions about diabetes were negative, and the top three negative ratios aspects were avoiding complications (7.60), problem-solving (4.08) and exercise (3.97). In terms of diet, the most popular topics were Chinese medicine and special diet therapy. In terms of life adjustment, financial issues, weight reduction, and a less painful glucometer were discussed the most. Furthermore, sexual dysfunction, neuropathy, nephropathy, and retinopathy were the most worrying issues in the avoiding complications area. Using text mining, we found that people care most about sexual dysfunction. Health providers care about the benefits of exercise in diabetes care, but people are mostly really concerned about sexual functioning. CONCLUSIONS A conceptual gap between health providers and diabetes patients existed in this real-world social media investigation. To spread healthy diabetic education concepts in the media, health providers might wish to provide more information related to patients actual areas of concern, such as sexual function, Chinese medicine, and weight reduction.

scholarly journals Use and Appropriation of Virtual Social Networks: Mexico and Spain, a Cross-Cultural Study

2017 ◽  
Vol 9 (1) ◽  
pp. 82
Author(s):  
Salvador Madrigal Moreno ◽  
Jaime Gil Lafuente ◽  
Gerardo Gabriel Alfaro Calderón ◽  
Flor Madrigal Moreno
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Cultural Study ◽  
Social Dynamics ◽  
Cross Cultural ◽  
Embryonic Stage ◽  
Cross Cultural Study ◽  
The Social ◽  
A Current

Virtual social networks (VSN) represent a phenomenon that continues reconfiguring the social dynamics. They have gone from the embryonic stage to a stage of maturity where it is observed that the context uses and appropriates those considered useful, giving them the use that seems to fit. Thus, Mexico and Spain contexts have specific characteristics and conditions. The aim of this study is to describe the access and appropriations of VSN, both in Mexico and in Spain and to show the challenges they face. The structure of this research is primarily an introduction to explain social networks as a current media phenomenon to later compare how each context has accessed, used and fitted these social networks into their own contexts. Finally, it will be discussed how Spain and Mexico face their challenges and last how each country treat the social media either as a threat or as an opportunity.

scholarly journals Study Designs for Quantitative Social Science Research Using Social Media

2020 ◽  
Author(s):  
Leticia Bode ◽  
Pamela Davis-Kean ◽  
Lisa Singh ◽  
Tanya Berger-Wolf ◽  
Ceren Budak ◽  
...  
Keyword(s):  
Social Media ◽  
Social Science ◽  
Computer Science ◽  
Quantitative Research ◽  
Social Science Research ◽  
Basic Research ◽  
Science Research ◽  
Social Media Data ◽  
Computer Scientists ◽  
Media Data

Social media provides a rich amount of data on the everyday lives, opinions, thoughts, beliefs, and behaviors of individuals and organizations in near real-time. Leveraging these data effectively and responsibly should therefore improve our ability to understand political, psychological, economic, and sociological behaviors and opinions across time. This article is the first in a series of white papers that will provide a summary of the discussions derived from meetings of social scientists and computer scientists with the goal of creating consensus for how social and computer science could converge to answer important questions about complex human behaviors and dynamics using social media data. We present three basic research designs that are commonly used in social science and are applicable to research using social media data: qualitative observation, experiments, and surveys. We also discuss a fourth design that is primarily informed by computer science, non-designed data, but that can inform social science research. After a brief discussion of the general approach of these designs and their applicability for use with social media data, we discuss the challenges associated with their use with social media data and potential solutions for “convergence” of these methods for future quantitative research in the social sciences.

New Data Sources in Social Science Research: Things to Know Before Working With Reddit Data

2019 ◽  
pp. 089443931989330 ◽  
Author(s):  
Ashley Amaya ◽  
Ruben Bach ◽  
Florian Keusch ◽  
Frauke Kreuter
Keyword(s):  
Social Media ◽  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Lessons Learned ◽  
Data Sources ◽  
Front Page ◽  
Social Media Data ◽  
New Research ◽  
Media Data

Social media are becoming more popular as a source of data for social science researchers. These data are plentiful and offer the potential to answer new research questions at smaller geographies and for rarer subpopulations. When deciding whether to use data from social media, it is useful to learn as much as possible about the data and its source. Social media data have properties quite different from those with which many social scientists are used to working, so the assumptions often used to plan and manage a project may no longer hold. For example, social media data are so large that they may not be able to be processed on a single machine; they are in file formats with which many researchers are unfamiliar, and they require a level of data transformation and processing that has rarely been required when using more traditional data sources (e.g., survey data). Unfortunately, this type of information is often not obvious ahead of time as much of this knowledge is gained through word-of-mouth and experience. In this article, we attempt to document several challenges and opportunities encountered when working with Reddit, the self-proclaimed “front page of the Internet” and popular social media site. Specifically, we provide descriptive information about the Reddit site and its users, tips for using organic data from Reddit for social science research, some ideas for conducting a survey on Reddit, and lessons learned in merging survey responses with Reddit posts. While this article is specific to Reddit, researchers may also view it as a list of the type of information one may seek to acquire prior to conducting a project that uses any type of social media data.

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