A Discussion Forum on

Weight Loss Programs: Social Network Analysis

Presented by: Xiaoqing Zhuang Steve Iduye

Agenda

• Background• Dataset Introduction• Two-Mode Network Analysis Degree Centrality Betweeness Centrality Closeness Centrality Eigenvector Centrlity• Conclusions•

Background

• Losing weight or maintaining weight.• Money, and time used• Weight loss programs (exercise, diet, medication, medical supervised program, surgery etc)• Online weight loss discussion forum: -Women only -Participants from all over the world

-At least one program• Prof. Raza provides us the dataset•

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Dataset Introduction

• 109 posts by 63 women users and 28 weight loss program

Objective: Analysis of the dataset focuses on: program popularity among users Effectiveness of the weight loss programsProgram accessibility to the usersSocial relationship between users and the programs on the

discussion forum.

Dataset Introduction• Sum

• Minimum

• Maximum•• Average

Dataset Introduction

Fig 1 Social network

Dataset Introduction

Tab1.1 Statistics of users (Rows) (User with highest sum is highlighted)

Tab1.2 Statistics of threads (Columns) (Thread with highest sum is highlighted)

Dataset Introduction

Two-Mode Network Analysis  ——Degree Centrality (Popularity)

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• Q1: Which weight loss program methods are you using or have you used?

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Two-Mode Network Analysis  ——Degree Centrality

Fig 2 Centrality measures for Degree Tab2 Highest Degree is highlighted

Two-Mode Network Analysis ——Betweeness Centrality (Effectiveness)

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• Q2: Which weight loss program works best for you (effective)?•

Two-Mode Network Analysis  ——Betweeness Centrality

Fig3 Centrality measures for Betweeness. Tab 3.1 Highest Betweeness is highlighted

Two-Mode Network Analysis ——Closeness Centrality (Available or Accessible)

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• Q3: Which weight loss program is readily available to women irrespective of their geographical location?

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Two-Mode Network Analysis  ——Closeness Centrality

Fig4 Centrality measures for ClosenessTab 4 Highest Closeness is highlighted

Two-Mode Network Analysis ——Eigenvector Centrality (Participants Connection with Important Programs)•

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• Q4: Which weight loss program would you use again or recommend to others?

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Two-Mode Network Analysis  ——Eigenvector Centrality

Fig 5 Centrality measures for Eigenvector

Tab 5 Highest Eigenvector is highlighted

Conclusions

From the used dataset and analysis:• Popularity of a certain weight loss program also means effectiveness

for everyone that uses it. • Certain weight loss program is tailored towards individual physical,

medical capabilities, or needs. • There is a preference in using a certain weight loss program over the

other based on many factors like location, and the type of programs others are using.

• A weight loss program that produces positive result would easily be recommended without hesitation.

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