Using Machine Learning to Compare the Information Needs and Interactions of Facebook: Taking Six Retail Brands as an Example

This study explores the interactive characteristics of the public, referencing existing data mining methods. This research attempts to develop a community data mining and integration technology to investigate the trends of global retail chain brands. Using social media mining and ensemble learning, it examines key image cues to highlight the various reasons motivating participation by fans. Further, it expands the discussion on image and marketing cues to explore how various social brands induce public participation and the evaluation of information efficiency. This study integrates random decision forests, extreme gradient boost, and adaboost for statistical verification. From 1 January 2011 to 31 December 2019, the studied brands published a total of 25,538 posts. The study combines community information and participation in its research framework. The samples are divided into three categories: retail food brand, retail home improvement brand, and retail warehouse club brand. This research draws on brand image and information cue theory to design the theoretical framework, and then uses behavior response factors for the theoretical integration. This study contributes a model that classifies brand community posts and mines related data to analyze public needs and preferences. More specifically, it proposes a framework with supervised and ensemble learning to classify information users′ behavioral characteristics.

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Extracting knowledge from building-related data — A data mining framework

Building Simulation ◽

10.1007/s12273-013-0117-8 ◽

2013 ◽

Vol 6 (2) ◽

pp. 207-222 ◽

Cited By ~ 36

Author(s):

Zhun Yu ◽

Benjamin C. M. Fung ◽

Fariborz Haghighat

Keyword(s):

Data Mining ◽

Related Data

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Prediction of Conversion from Mild Cognitive Impairment to Alzheimer Disease Based on Bayesian Data Mining with Ensemble Learning

The Neuroradiology Journal ◽

10.1177/197140091202500101 ◽

2012 ◽

Vol 25 (1) ◽

pp. 5-16 ◽

Cited By ~ 7

Author(s):

R. Chen ◽

K. Young ◽

L.L. Chao ◽

B. Miller ◽

K. Yaffe ◽

...

Keyword(s):

Data Mining ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Alzheimer Disease ◽

Ensemble Learning

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How have governments supported citizens stranded abroad due to COVID-19 travel restrictions? A comparative analysis of the financial and health support in eleven countries

10.21203/rs.3.rs-923608/v1 ◽

2021 ◽

Author(s):

Pippa McDermid ◽

Adam Craig ◽

Meru Sheel ◽

Holly Seale

Keyword(s):

Information Needs ◽

Design Tool ◽

Government Support ◽

Website Design ◽

Global Public Health ◽

Related Data ◽

Related Information ◽

Travel Restrictions ◽

Health Support ◽

Content Accessibility

Abstract Background: In response to the continuing threat of COVID-19, many countries have implemented some form of border restriction. A repercussion of these restrictions has been that some travellers have been stranded abroad unable to return to their country of residence, and in need for government support. Our analysis explores the COVID-19-related information and support options provided by 11 countries to their citizens stranded overseas due to travel restrictions. We also examined the quality (i.e., readability, accessibility, and useability) of the information that was available from selected governments’ web-based resources.Methods: Between June 18 to June 30, 2021, COVID-19-related webpages from 11 countries (Australia, New Zealand, Fiji, Canada, United States of America (USA), United Kingdom (UK), France, Spain, Japan, Singapore, and Thailand) were reviewed and content relating to information and support for citizens stuck overseas analysed. Government assistance-related data from each webpage was extracted and coded for the following themes: travel arrangements, health and wellbeing, finance and accommodation, information needs, and sources. Readability was examined using the Simplified Measure of Gobbledygook (SMOG) and the Flesch Kincaid readability tests; content ‘accessibility’ was measured using the Web Content Accessibility Guidelines (WCAG) Version 2.1; and content ‘usability’ assessed using the usability heuristics for website design tool.Results: Ninety-eight webpages from 34 websites were evaluated. No country assessed covered all themes analysed. Most provided information and some level of support regarding repatriation options; border control and re-entry measures; medical assistance; and traveller registration. Only three countries provided information or support for emergency housing while abroad, and six provided some form of mental health support for their citizens. Our analysis of the quality of COVID-19-related information available on a subset of four countries’ websites found poor readability and multiple accessibility and usability issues.Conclusion: With large variance in the information and services available across the countries analysed, our results highlight gaps, inconsistencies, and potential inequities in support available, and raise issues pertinent to the quality, accessibility, and usability of information. This study will assist policymakers plan and communicate comprehensive support packages for citizens stuck abroad due to the COVID-19 situation and design future efforts to prepare for global public health emergencies.

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Intelligent Portals for Supporting Medical Information Needs

Web Portals ◽

10.4018/978-1-59140-438-5.ch013 ◽

2011 ◽

pp. 270-296 ◽

Cited By ~ 2

Author(s):

Jane Moon ◽

Frada Burstein

Keyword(s):

Decision Making ◽

Web Sites ◽

Information Seeking ◽

Information Needs ◽

Medical Information ◽

Care Delivery ◽

Internet Usage ◽

Medical Decisions ◽

Community Information ◽

Decision Making Processes

The aim of this chapter is to review the way portal technology can assist users seeking medical information. There has been an increase in health Internet usage, and better health-care delivery outcomes are predicted as users are better informed when making medical decisions. At the same time, there is much concern about the need for medical portals to meet community information needs. This chapter discusses what constitutes an intelligent portal, discusses desirable portal components and attributes of intelligent portal features, and how these can be implemented to meet the needs of diverse users. Seven Australian medical Web sites have been analysed according to intelligence features. The results and analysis are presented and discussed, in particular, with respect to their functionality as defined for intelligent portals. The discussion is focused on the extent to which these attributes help users with their information seeking and therefore support their decision-making processes.

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Decision trees, knowledge rules and some related data mining algorithms

SOFSEM'96: Theory and Practice of Informatics - Lecture Notes in Computer Science ◽

10.1007/bfb0037419 ◽

1996 ◽

pp. 369-376

Author(s):

Jia Liang Han

Keyword(s):

Data Mining ◽

Decision Trees ◽

Related Data ◽

Data Mining Algorithms ◽

Knowledge Rules ◽

Mining Algorithms

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MVClustViz

International Journal of System Dynamics Applications ◽

10.4018/ijsda.2013100102 ◽

2013 ◽

Vol 2 (4) ◽

pp. 19-32

Author(s):

Sagar S. De ◽

Minati Mishra ◽

Satchidananda Dehuri

Keyword(s):

Data Mining ◽

Large Volume ◽

Visual Data ◽

Visual Data Mining ◽

Visualization Technique ◽

Projection Technique ◽

Range Analysis ◽

Related Data ◽

Multiple Dimension

In the visual data mining, visualization of clusters is a challenging task. Although lots of techniques already have been developed, the challenges still remain to represent large volume of data with multiple dimension and overlapped clusters. In this paper, a multivariate clusters visualization technique (MVClustViz) has been presented to visualize the centroid-based clusters. The geographic projection technique supports multi-dimension, large volume, and both crisp and fuzzy clusters visualization. This technique is most suitable for range analysis of defense related data.

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Community Information Needs: A W.A. Study

Media Information Australia ◽

10.1177/1329878x7700500109 ◽

1977 ◽

Vol 5 (1) ◽

pp. 23-24

Author(s):

Jim Macbeth

Keyword(s):

Information Needs ◽

Community Information

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Semantic Integration and Knowledge Discovery for Environmental Research

Successes and New Directions in Data Mining ◽

10.4018/978-1-59904-645-7.ch010 ◽

2008 ◽

pp. 213-235

Author(s):

Zhiyuan Chen ◽

Aryya Gangopadhyay ◽

George Karabatis ◽

Michael McGuire ◽

Claire Welty

Keyword(s):

Data Mining ◽

Knowledge Discovery ◽

Semantic Network ◽

Semantic Integration ◽

Environmental Data ◽

Data Sources ◽

Environmental Research ◽

Related Data ◽

Use Of Data ◽

Data Semantics

Environmental research and knowledge discovery both require extensive use of data stored in various sources and created in different ways for diverse purposes. We describe a new metadata approach to elicit semantic information from environmental data and implement semantics-based techniques to assist users in integrating, navigating, and mining multiple environmental data sources. Our system contains specifications of various environmental data sources and the relationships that are formed among them. User requests are augmented with semantically related data sources and automatically presented as a visual semantic network. In addition, we present a methodology for data navigation and pattern discovery using multi-resolution browsing and data mining. The data semantics are captured and utilized in terms of their patterns and trends at multiple levels of resolution. We present the efficacy of our methodology through experimental results.

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