Web-SeminárioAnalytics em Mídia

SociaisUma aplicação na Saúde e

CRMWeb-SeminárioSocial Media Analytics

Applying in Health & CRMUsing 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 oldinterested in:

● Cars● Technology● Cultural events

Modern

Marta, 28 years oldInterested in:

● Beauty● Fashion● Tourism - Extreme Sports● Dance

Sportsman

Guilherme, 19 years oldInterested 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.

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

What ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

Health insurance Companies

What ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

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

Source: UOL

What ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

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 ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

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?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

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 ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

Processing - Sentiment Analysis

This workflow develops sentiment analysis (in the example based on Unimed term).

As in the previous example, the search andtext mining processing and sentiment analysis can be made in real time.

Download Workflow What? Part - II

What ?Getting information from Social Media

Application of Text Mining and Sentiment Analysis

GettingTags

NodeOSM 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

Getting overview of the network of relationships these people.How ?

Find friends in common among users.

Getting overview of the network of relationships these people.How ?

The hidden influence of social network.

Excerpt of talk at TED

Click for see

Getting overview of the network of relationships these people.How ?

3:19

degree of separation

Probability of a person becoming overweight given the social contact with obese

1 2 34 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

Getting overview of the network of relationships these people.How ?

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%.

Getting overview of the network of relationships these people.How ?

ReferencesBook:

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 EstanislaoSkype: marcus.estanislaoTel: +55(11) 32805760Cel: +55(11) 968376661 @EstanislaoMVMarcus (at) estanislao.com.br

Thank you very much!