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Augmenting geovisual analytics of social media data with heterogeneous information network mining-Cognitive plausibility assessment.

ABSTRACT: This paper investigates the feasibility, from a user perspective, of integrating a heterogeneous information network mining (HINM) technique into SensePlace3 (SP3), a web-based geovisual analytics environment. The core contribution of this paper is a user study that determines whether an analyst with minimal background can comprehend the network data modeling metaphors employed by the resulting system, whether they can employ said metaphors to explore spatial data, and whether they can interpret the results of such spatial analysis correctly. This study confirms that all of the above is, indeed, possible, and provides empirical evidence about the importance of a hands-on tutorial and a graphical approach to explaining data modeling metaphors in the successful adoption of advanced data mining techniques. Analysis of outcomes of data exploration by the study participants also demonstrates the kinds of insights that a visual interface to HINM can enable. A second contribution is a realistic case study that demonstrates that our HINM approach (made accessible through a visual interface that provides immediate visual feedback for user queries), produces a clear and a positive difference in the outcome of spatial analysis. Although this study does not aim to validate HINM as a data modeling approach (there is considerable evidence for this in existing literature), the results of the case study suggest that HINM holds promise in the (geo)visual analytics domain as well, particularly when integrated into geovisual analytics applications. A third contribution is a user study protocol that is based on and improves upon the current methodological state of the art. This protocol includes a hands-on tutorial and a set of realistic data analysis tasks. Detailed evaluation protocols are rare in geovisual analytics (and in visual analytics more broadly), with most studies reviewed in this paper failing to provide sufficient details for study replication or comparison work.

SUBMITTER: Savelyev A

PROVIDER: S-EPMC6279051 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Augmenting geovisual analytics of social media data with heterogeneous information network mining-Cognitive plausibility assessment.

Savelyev Alexander A MacEachren Alan M AM

PloS one 20181204 12

This paper investigates the feasibility, from a user perspective, of integrating a heterogeneous information network mining (HINM) technique into SensePlace3 (SP3), a web-based geovisual analytics environment. The core contribution of this paper is a user study that determines whether an analyst with minimal background can comprehend the network data modeling metaphors employed by the resulting system, whether they can employ said metaphors to explore spatial data, and whether they can interpret ...[more]

PMID: 30513083

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Project description:IntroductionChronic kidney disease (CKD), which affects about 10% of global population, has become a global public health crisis in recent decades. It is well recognized that health information dissemination could change health behaviors, thereby greatly improving the early diagnosis and prevention of diseases. Due to fast dissemination, wide audience, intuitive and vivid, popularization through short videos has rapidly developed into the new main battlefield of health information. The objective of this study was to describe the properties of the CKD-related health information on short video apps.MethodsSearching on short video apps with high-frequency words in kidney disease as keywords, the basic information of the uploaders was retrieved and extracted short video. Five quality dimensions, awareness, popularity, utility, validity and quality, of each video were assessed with numeric rating scale (NRS) by five volunteers with CKD and three nephrologists.ResultsFrom the platform of douyin, 65 uploaders and their 3973 short videos of CKD-related health information were investigated in this study. Most information of short videos had relatively high level in awareness, popularity and utility assessment, but some information had relatively low level in validity and quality assessment; 24 (36.9%) uploaders were from governmental hospital (tertiary hospital); 19 uploaders (29.2%) uploaded more than 100 short videos and 49 uploaders (75.4%) updated their videos weekly, and 16 uploaders (24.6%) didn't update short videos more than one month. There were 4 uploaders (6.2%) have more than 1 million follows, and 39 uploaders (60%) had follows less than 10,000. "Lifestyles", "Common symptoms of kidney disease" and "Nephritis or kidney disease" were the three main contents of these short videos. The comprehensive data of uploaders with millions of follows in nephrology specialty were much lower than that of orthopedics and other specialty.ConclusionThe validity and quality of short video is still unsatisfactory, and CKD-related health information also need to be led and improved, although the awareness, popularity, and utility of health information about CKD is acceptable. The public should be selective and cautious in seeking CKD information on social media.

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Dataset Information

Augmenting geovisual analytics of social media data with heterogeneous information network mining-Cognitive plausibility assessment.

Publications

Augmenting geovisual analytics of social media data with heterogeneous information network mining-Cognitive plausibility assessment.

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