This document discusses conducting sentiment analysis to improve customer-centric approaches with Python. It defines sentiment analysis as the field of studying people's opinions, sentiments, appraisals, attitudes, and emotions toward entities expressed in text. The benefits of sentiment analysis for improving customer service are discussed, such as identifying emotional triggers, adaptive customer service, and reducing customer churn. Examples of using sentiment analysis for brand monitoring and social media monitoring are provided. An overview of natural language processing techniques for sentiment analysis is given, including text preprocessing, word clouds, removal of stopwords and punctuation, and modeling approaches like Naive Bayes, K-NN, decision trees, logistic regression, and deep learning.

1. Conduct Sentiment Analysis to Improve Customer
Centric with Python
Dr. Windu, Gata, M.Kom

2. Internal Trainer Multimatics
IT Consultant since 1995
Lecturer since 2003
Computer Researcher 2008
Dr. Windu Gata, M.Kom
Profile

3. Sentimen
Sentimen/sen·ti·men/ /séntimén/
1 n pendapat atau pandangan yang
didasarkan pada perasaan yang berlebih-
lebihan terhadap sesuatu (bertentangan
dengan pertimbangan pikiran): keputusan
yang dihasilkan akan tidak adil jika disertai
rasa -- pribadi;
2 n emosi yang berlebihan: rasa -- sebagai
bangsa Indonesia akan tumbuh kuat jika
kita jauh dari negeri ini;
3 a cak iri hati; tidak senang; dendam;
4 n reaksi yang tidak
menguntungkan: penurunan harga saham
hanya disebabkan oleh -- pasar
Definisi sentimen : ks, iri hati, tidak senang; dendam.

4. Sentiment
Data from Oxford Languages

5. Sentiment Analysis
• Sentiment Analysis, also called opinion mining, is the
field of study that analyzes people's opinions,
sentiments, appraisal, attitude, and emotions toward
entities and their attributes expressed in written text.
• Sentiment analysis is an analytical approach, which
is used for text analysis. The aim of sentiment
analysis ito determine the opinion and subjectivity of
any opinion, review or tweet

6. Sentiment Analysis
Source: What is Sentiment Analysis and How Does It Work? - REEA GLOBAL

7. Benefit Sentiment Analysis to Improve Customer Centric
Source Source 2
Upselling
Opportunities
Agent Monitoring Training Chatbot Identifying key emotional triggers Handling multiple customers
Adaptive customer
service
Live Insight
Live Insight Quick Escalation Reduce customer
churn
Tracking overall customer satisfaction

8. Example Usages of Sentiment Analysis
Souce 2018
Nike – Brand Monitoring
Customers Love Being Heard
#justburnit
Souce
Take Nike’s recent marketing campaign involving controversial
National Football League quarterback Colin Kaepernick

9. Example Usages of Sentiment Analysis
Source
Positive sentiment for
Nike actually increased
after the controversial ad
was released. In fact,
Nike’s overall sales
jumped more than 31%.

10. Example Usages of Sentiment Analysis
Keeping an Eye on Your Competition
McDonalds vs. Burger King
Souce Because of parodi

11. Example Usages of Sentiment Analysis
Souce
Social Media
Monitoring –
US Airline 2015
Souce 2

12. Sentiment Analysis
Natural Languange Processing (NLP)

13. Natural Language Processing
SENTENCE
TEXT PROCESSING
ALGORITHM
EVALUATION
TEXT (Unstructure)

14. Python Library and other
matplotlib
Wordcloud GataFramework

15. Yuk Ngoding Python !!
Persiapan:
- Anaconda
- Jupiter Notebook
- Atau Spyder
- Google Colab
- New Notebook

16. NLP - Start
Saya Sedang Berpergian ke Pasar
membeli ikan, karena saya suka
banget sama ikan
Text – Unstructured Data
[
'Saya’,
'Sedang’,
'Berpergian’,
'ke’,
'Pasar’,
'membeli’,
'ikan’,
',’,
'karena’,
'saya’,
'suka’,
'banget’,
'sama’,
'ikan’
]
Array

17. NLP – Start

18. NLP – Frequency of Words
vartext = str.lower(vartext)
Transform Cases → Change to lower case

19. NLP – Plot the Graph

20. NLP – Remove Punctuation

21. NLP – Stopwords Using Spacy

22. NLP – Stopwords Using NLTK

23. NLP – Word Cloud

24. NLP – Remove # dan @

25. NLP – Stemming Indonesia (Sastrawi)

26. NLP – Preprocessing Indonesia (Gataframework)

27. NLP – Contoh Data
https://drive.google.com/file/d/1KtrR02nHzed1UpgjntpOkyML7qW7ZGYc/view?usp=sharing

28. NLP – Persiapan Data

29. NLP – Visualisasi

30. NLP – Preprocessing - Gata

31. NLP – Preprocessing

32. NLP – Training Testing – SVM Model

33. NLP – Evaluation

34. NLP – Testing New Data

35. Naïve Bayes

36. K-NN

37. Decision Tree

38. Logistic Regression

39. Deep Learning – Load Data

40. Deep Learning – Model Summary

41. Deep Learning – Model Fit

42. Deep Learning - Predict

43. Literature
• Liu, B. 2020. Sentiment Analysis - Mining
Opinions, Sentiments, and Emotions. Cambridge
University Press
• Rajput, D. D., et al. 2018. Sentiment Analysis
and Knowledge Discovery in Contemporary
Business
• http://www.gataframework.com
• Google Images