Ward's method is a hierarchical clustering algorithm that can be used to group issues or other items into statistically similar clusters. It works by minimizing the variance between clusters at each step as items are grouped together. The document provides an example of using Ward's method to analyze issues and arrive at voter segments by clustering voters based on the issues that are most important to them. A dendrogram visualizing the final voter clusters is shown to aid in decision making.

1. Clustering Analysis of Issues
to arrive at Voter Segments
Aashish Juneja Ph.D

2. Ward’s method- Introduction
• Ward’s Method is a quantitative approach that clusters things
or helps in grouping things whose qualities were statistically most
similar.
• Representative Use Cases:
• Clusters of Emerging Markets
• Clusters of Stocks (e.g Cluster of mid cap stocks)
• Clusters of Issues - Elections
• Cluster of Companies that are takeover targets (M&A)
• Cluster of employees based on psychographic variables/performance
traits/demographics

3. Hierarchical Clustering (Ward’s method) for identifying
issue clusters
• Average Linkage
• Clustering criterion based on
the average distance
• Ward's Method
• Based on the loss of
information resulting from
grouping of the objects into
clusters (minimize within
cluster variation)
3

4. Ward’s method- Some traits
Agglomerative Clustering Algorithm
Ward's method starts with n clusters of size 1 and continues until all the observations are included into
one cluster
Example: Ward’s method will start with leaves and reach to truck. It looks for groups of leaves that it forms
into branches, the branches into limbs and eventually into the trunk

5. Visual- Ward’s method for arriving at Voter
Clusters

6. Dendogram showing Voter segments arrived at
using Ward’s method-Final Visual for decision
making

7. Leveraging Social Psychology
• Agenda Setting
• Issue Framing
• Issue Salience
• Agenda Crowding
• Persuasion- CRASS-L Framework
• Optimism