socialRadius: Visual Exploration of User Check-in Behavior Based on Social Media Data

Wen, Changjiang; Teng, Zhiyao; Chen, Jian; Wu, Yifan; Gong, Rui; Pu, Juan

doi:10.1007/978-3-319-46771-9_39

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Another study in South African business showed the high value of VATs in day-to-day operations [26]. Besides, these decision support function deriving from VATs also emerges in the areas of online product review [37], changes in consumer behavior [27,29,30], supply chain network [8,25,32], health enhancement [33,35], pipeline maintenance [34], and retailing management [31].…”

Section: Rq1: What Is the Definition Concerning Vats And Howmentioning

confidence: 99%

Introducing Business Visual Analytics into Business Education by Information Technology and Computing Methods

Yu-yu

Chan²,

Liu

2022

Mobile Information Systems

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Business students feel an urgency to be competent involving business intelligence in their studies and career. This study examines the current literature on business visual analytic technologies (VATs), both in the business community and in business learning, and points out consideration as a research gap in the existing literature. We conduct a systematic review with database searches from 2006 to 2020. The objectives of the review are to identify (a). the existing terminologies related to VATs in the literature; (b). the purpose of VAT application and the benefits of VATs in the business community; and to examine (c). how the VATs are related to the educational context, particularly, in business learning. The findings indicate that VATs provide positive enhancement in business analytics; however, the effect of VAT application in business learning is rather limited. We provide insights for further studies involving VAT-enhanced business learning.

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Section: Rq1: What Is the Definition Concerning Vats And Howmentioning

confidence: 99%

Introducing Business Visual Analytics into Business Education by Information Technology and Computing Methods

Yu-yu

Chan²,

Liu

2022

Mobile Information Systems

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“…Moreover, Pu et al (2016) focused on the valuable geo-location data available in social media applications by introducing the 'Social Check-in Fingerprinting (Sci-Fin)' tool which offers organisations "the opportunity to capture and analyze users' spatial and temporal behaviors" through social network check-in data. Respectively, Wen et al (2016) suggested an alternative VA system, called 'SocialRadius' that can interactively explore spatio-temporal features and check-in activities, in a variety of applications, ranging from BI applications to transportation and information recommendation systems. Meanwhile, Kucher et al (2014;2016) presented a VA tool for social media textual data that "can be used to investigate stance phenomena and to refine the so-called stance markers collection" with respect to sentiment and certainty.…”

Section: Visual Analyticsmentioning

confidence: 99%

Social business intelligence: Review and research directions

Gioti¹,

Ponis²,

Panayiotou³

2018

JISIB

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Social business intelligence (SBI) is a rather novel discipline, emerged in theacademic and business literature as a result of the convergence of two distinct researchdomains: business intelligence (BI) and social media. Traditional BI scientists and practitioners,after an inevitable initial shock, are currently discovering and acknowledge the potential of usergenerated content (UGD) published in social media as an invaluable and inexhaustible sourceof information capable of supporting a wide range of business activities. The confluence of thesetwo emerging domains is already producing new added value organizational processes andenhanced business capabilities utilized by companies all over the world to effectively harnesssocial media data and analyze them in order to produce added value information such ascustomer profiles and demographics, search habits, and social behaviors. Currently the SBIdomain is largely uncharted, characterized by controversial definitions of terms and concepts,fragmented and isolated research efforts, obstacles created by proprietary data, systems andtechnologies that are not mature yet. This paper aspires to be one of the few -to our knowledge contemporaryefforts to explore the SBI scientific field, clarify definitions and concepts,structure the documented research efforts in the area and finally formulate an agenda of futureresearch based on the identification of current research shortcomings and limitations.

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Temporal aggregation bias and Gerrymandering urban time series

Stehle

2021

Geoinformatica

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socialRadius: Visual Exploration of User Check-in Behavior Based on Social Media Data

Cited by 4 publications

References 15 publications

Introducing Business Visual Analytics into Business Education by Information Technology and Computing Methods

Introducing Business Visual Analytics into Business Education by Information Technology and Computing Methods

Social business intelligence: Review and research directions

Temporal aggregation bias and Gerrymandering urban time series

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