Social Media Anlytics

Web-Seminário
Analytics em Mídia Sociais
Uma aplicação na Saúde e CRM
Web-Seminário
Social Media Analytics
Applying in Health & CRM
Using KNIME

Agenda
Getting overview of the network of relationships these
people.
Having better understanding about characteristics of
customers.
Who ?
What ?
How ?
Getting information from Social Media
Application of Text Mining and Sentiment Analysis

Purpose of CRM
Identify each customer, differentiate the best, know their profiles and preferences, and interact with
every customer in order to increase:
● Customer value
● Value for the company
CRM
Know the customers makes a difference

Sophisticated
Carlos, 35 years old
interested in:
● Cars
● Technology
● Cultural events
Modern
Marta, 28 years old
Interested in:
● Beauty
● Fashion
● Tourism - Extreme Sports
● Dance
Sportsman
Guilherme, 19 years old
Interested in
● Running
● Travel - Beach
● Sports
Customers tend to be more satisfied when the company interacts with them in the way that suits
them and offers products and services that really interest them.
Knowledge as an asset

All information about the customer, is in the company's database?
Even although, the model presents a good fitting results, there are
several relevant information about the client that are not in the
databases of the company.
It is not uncommon, professionals
develop their jobs based on the
idea that most of the information
about the customer is in the
company's database.

Network of Facebook users.
Paul Butler, a Facebook engineer, interested in checking how country's borders affect friendships
around the world, developed a facebook users Relationship network.
More Informations

- 76 million users on Facebook
- Twitter 42 million users
- 490 million views, with 8 million unique visitors/month
Fonte Reuters
Statistics Brazil

Understanding social network
Not only the individual characteristics are important for
understanding the behavior of people.
Studies have found that social networks influence and are
influenced by individuals.
Thus understanding these networks is essential to increase the
understanding of people's behavior.
So new drivers should be considered:
● Content, direction and strength
● Social ties (connecting pairs of players via one or more relationship)
● Multiplexity
● Composition of the social bond
See this post (in portuguese)

Getting data from conventional sources plus from Web.

What ?

Health insurance
Companies
What ?

Agency monitors the opinion of Internet users about athletes of a football team, and Adriano is
the no. 1 target.
Source: UOL
What ?
What

Processing - Search the terms
The workflow (Getting social networks) develops search terms (in the example: Health Plan
and Health Insurance), then processes Text mining techniques and shows a Tag Cloud.
The search for this and any other term,
and its processing may be done in real time.
What ?

Before you download and process workflows.
If you are not familiar with KNIME, I suggest first see the following videos:
Introduction to KNIME Getting information from Twitter
Download Workflow What? Part - I
Click to view
the Video
O que?

Briefly, sentimental analysis is:
a process that involves Text mining methods, where the goal
is to identify which terms that were extracted from a given text
represent positive or negative sentiment about a topic or a
particular context.
What ?

Processing - Sentiment Analysis
This workflow develops sentiment analysis (in the example based on Unimed term).
As in the previous example, the search and
text mining processing and sentiment analysis
can be made in real time.
Download Workflow What? Part - II
What ?

Getting
Tags
Node
OSM Map View
Having better understanding about characteristics of customers.Quem?

● Acquire a global view of the network
● Overview of some metrics
● View
● Clusters
Having better understanding about characteristics of customers.Quem?

Getting friends of each user
Relationship
network
Getting overview of the network of relationships these people.How ?

Network View

Find friends in
common among
users.

The hidden influence of social network.
Excerpt of talk at TED
Click for see

degree of separation
Probability of a
person
becoming
overweight given
the social
contact with
obese
1 2 3
4 5
Y axis represents the risk of a person being overweight because of their social contact with obese.
X-axis represents the degree of separation between the two people
60
50
40
30
20
10
0

The study found that:
If a person has a social contact directly with an obese person (one degree of
separation), the risk of becoming obese is 50%.
or
If this person has contact with a person who in turn has contact with an obese (= two
degrees of separation) the risk of this person becoming obese is 25%.

References
Book:
Valente, Thomas W. (2010-02-25). Social Networks and Health: Models, Methods, and Applications (Kindle
Locations 4-5). Oxford University Press. Kindle Edition.
White Papers
● Usable Customer Intelligence from Social Media Data: Network Analytics meets Text Mining
Text mining and network analytics are combined here to better position negative and positive users in
context with their weight as influencers or followers inside the discussion forum.
Download pdf
● The KNIME Text Processing Feature: An Introduction
This technical report explains the fundamentals of text processing feature in KNIME along with detailed
descriptions and examples of all key node categories.
Download pdf
Post
● Social Network Analysis in KNIME for R users.
Material KNIME
● Material
● How to get Twitter Data into KNIME

Marcus Estanislao
Skype: marcus.estanislao
Tel: +55(11) 32805760
Cel: +55(11) 968376661
@EstanislaoMV
Marcus (at) estanislao.com.br
Thank you very much!

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