msg.aiLearning customer service through

topic modeling of tweetsPeter Frick

Can machine learning improve social customer interactions?

Leveraging LDA to learn tweet topicsAirline

tweets

Leveraging LDA to learn tweet topics

Terrible!! The worst flight ever! The pretzels and peanuts were bad

Airline tweets

Leveraging LDA to learn tweet topics

Terrible!! The worst flight ever! The pretzels and peanuts were bad

topic3

topic1

topic2

Latent Dirichlet

Allocation (LDA)

Airline tweets

WorstFailTerrible

Leveraging LDA to learn tweet topics

Terrible!! The worst flight ever! The pretzels and peanuts were bad

Airline tweets

Latent Dirichlet

Allocation (LDA)

topic3

topic1

topic2

WorstFailTerrible

Learning tweet topics using LDA

Good customer service

Using topics to estimate airline customer service

Topic 2

Tweets passing filter

Ranking airlines by Topic 2“bad customer service”

Using topics to estimate airline customer service

Ranking airlines by relativebad customer service

Predicted customer service matches recently published results

Source: 2015 J.D. Power North America AirlineSatisfaction Traditional Airline Rankings

J.D. Power rankings Ranking airlines by relativebad customer service

PredictionModel input

020

4060

8010

0

Varying µ−2

02

46

Popu

latio

n do

ublin

gs

DIP rate(doublings/h)

Time in erl (d)−0.04 0.00 0.04

020

4060

8010

0

0 5 10 15 20 25 30

−20

24

6Dens

ity 2µ

µ

0.5µ

0.5σ

σ

2σVarying σ

PredictionModel input

020

4060

8010

0

Varying µ

−20

24

6Po

pula

tion

doub

lings

DIP rate(doublings/h)

Time in erl (d)−0.04 0.00 0.04

020

4060

8010

0

0 5 10 15 20 25 30

−20

24

6Dens

ity 2µ

µ

0.5µ

0.5σ

σ

2σVarying σ

Peter Frick

Data pipeline

Msg.ai tweets

LDA  ModelCleaned  data

Pandas

NLTK

Topic  visualization

Kaggle tweets

pyLDAvis

Topic  Prediction