Taming Big Data: Using App Technology to Survey Social Media Users

Bail, Christopher A.

doi:10.2139/ssrn.2423608

Cited by 14 publications

(18 citation statements)

References 39 publications

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“…Prospective research studies are suggested to determine whether the excessive use of social media creates a causal risk of stress, anxiety depression, and other health symptoms and whether the negative aspects of social media are related to health impairment [60]. Regarding the positive contribution of social media, social media applications in the medical field, educational institutions, service organizations, fashion industry, tourism, and social interactions are helpful [140]. The technical contributions of social media are vast.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan

et al. 2019

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In today’s world, social media is playing an indispensable role on the learning behavior of university students to achieve sustainable education. The impact of social media on sustainable education is becoming an essential and impelling factor. The world has become a global village and technology use has made it a smaller world through social media and how it is changing instruction. This original study is amongst the few to perform a focalized investigation on revealing the relationship between positive and negative characteristics of social media and the learning attitude of university students for sustainable education. However, this study aims to examine the constructive and adverse factors that impact on students’ minds and how these helped students to share positive and negative aspects with others. It is increasingly noticeable that social networking sites and their applications present enormous benefits for as well as risks to university students and their implications on students’ psychological adjustment or learning behaviors are not well understood. This study adapted the cluster sampling method, and respondents participated from five selected regions. Researchers distributed 1013 questionnaires among the targeted sample of university students with an age range of 16 to 35 years, and they collected 831 complete/valid responses. This study applied the social gratification theory to examine students’ behavior practicing social media usage. This study specifically identified 18 adversarial and constructive factors of social media from the previous literature. The findings revealed that the usage of social media in Pakistan has a negative influence on a student’s behavior as compared to positive aspects. Results may not be generalized to the entire student community as findings are specific to the specific respondents only. This study presents a relationship between antithetical and creative characteristics of social media and exhibits avenues for future studies by facilitating a better understanding of web-based social network use.

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Section: Discussionmentioning

confidence: 99%

The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan

et al. 2019

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“…The type of big data we focus on does not come from a heavily theorized and well-planned scientific research project-they "are not the output of instruments designed to produce valid and reliable data amenable for scientific analysis"-which, at a minimum, creates discomfort among social scientists [5,11]. Instead, it is a byproduct of other activity, which "has led some scholars to ask whether [big] data can provide anything beyond crude description" [12]. Without additional contextual information to help "tame" it, the concern is such data will remain too "wild" for answering valuable questions of interest in the academic social sciences.…”

Section: Our Argument: a Roadmapmentioning

confidence: 99%

“…In general, the primary means of assessing and increasing the validity and value of data in the social sciences is undertaken through data augmentation. Examples of past big data augmentation include converting less structured data to more analytically tractable forms, linking multiple existing data sources [37] or collecting additional variables to check for spurious relationships or causal mechanisms [12,38]. As reviewed above, there are both manual and automated approaches to data augmentation, but neither is likely to be sufficient to both scale to the problems posed by big data and address social science skepticism about it.…”

Section: Big Data Skepticism In the Social Sciencesmentioning

confidence: 99%

“…Instead, we focus on a third option that can enhance both automated and manual approaches to data augmentation: using online crowdsourcing marketplaces such as Amazon Mechanical Turk (MTurk). Our work thus seeks to popularize and formalize a new tool within the nascent set of methodologies designed to increase the value and validity of online data collection efforts [12,39].…”

Section: Big Data Skepticism In the Social Sciencesmentioning

confidence: 99%

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Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and opportunities

2020

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Proponents of big data claim it will fuel a social research revolution, but skeptics challenge its reliability and decontextualization. The largest subset of big data is not designed for social research. Data augmentation-systematic assessment of measurement against known quantities and expansion of extant data with new information-is an important tool to maximize such data's validity and research value. Using trained research assistants or specialized algorithms are common approaches to augmentation but may not scale to big data or appease skeptics. We consider a third alternative: data augmentation with online crowdsourcing. Three empirical cases illustrate strengths and limitations of crowdsourcing, using Amazon Mechanical Turk to verify automated coding, link online databases, and gather data on online resources. Using these, we develop best practice guidelines and a reporting template to enhance reproducibility. Carefully designed, correctly applied, and rigorously documented crowdsourcing help address concerns about big data's usefulness for social research.

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“…3 Why twitter? Growing evidence from social and computer science points to the promising potential of social media data for social research (Bail, 2017;DiGrazia, McKelvey, Bollen, & Rojas, 2013;Flores, 2017;Liu et al, 2017;Mislove, Lehmann, Ahn, Onnela, & Rosenquist, 2011;Schwartz & Ungar, 2015;Sutton et al, 2014;Wei, Kenneth, Huan, & Kathleen, 2015). For example, Flores (2017) used Twitter to assess individuals' subjective sentiment toward immigration after the adoption of the controversial immigration bill in Arizona, SB 1070.…”

Section: Community Subjective Well-beingmentioning

confidence: 99%

Do National Service Programs Improve Subjective Well-Being in Communities?

Velasco

Paxton

Ressler

et al. 2018

The American Review of Public Administration

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Since the creation of Volunteers in Service to America (VISTA) in 1964 and AmeriCorps in 1993, a stated goal of national service programs has been to strengthen the overall health of communities across the United States. But whether national service programs have such community effects remains an open question. Using longitudinal cross-lagged panel and change-score models from 2005 to 2013, this study explores whether communities with national service programs exhibit greater subjective well-being. We use novel measures of subjective well-being derived from tweeted expressions of emotions, engagement, and relationships in 1,347 U.S. counties. Results show that national service programs improve subjective well-being primarily by mitigating threats to well-being and communities that exhibit more engagement are better able to attract national service programs. Although limited in size, these persistent effects are robust to multiple threats to inference and provide important new evidence on how national service improves communities in the United States.

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Taming Big Data: Using App Technology to Survey Social Media Users

Cited by 14 publications

References 39 publications

The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan

The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan

Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and opportunities

Do National Service Programs Improve Subjective Well-Being in Communities?

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