Question 1

A frequency bar chart technique counts the occurrence of words in a document while ignoring the order or the grammar of words.

Accepted Answer

A) True 
 B)False  False

Question 2

Summarize practitioner Jasmine Jones's views about the potential for natural language processing in marketing.

Accepted Answer

Practitioner Jasmine Jones believes that natural language processing has a huge potential in marketing. She emphasizes that NLP can be used to analyze customer feedback, social media posts, and other forms of communication to better understand consumer preferences and trends. Jones also highlights the ability of NLP to personalize marketing content and automate customer service interactions, leading to improved customer satisfaction and loyalty. Overall, she sees natural language processing as a valuable tool for marketers to enhance their strategies and effectively connect with their target audience.

Question 3

In the preprocessing step of text analytics, ________ is the process of removing prefixes or suffixes from words to reduce them to their root form.

Accepted Answer

A)  stop words removal 
B)  bag of words 
C)  stemming 
D)  lemmatization 
A)  stop words removal 
B)  bag of words 
C)  stemming 
D)  lemmatization C

Question 4

Explain the lemmatization technique of text analytics and provide several examples.

Accepted Answer

Lemmatization is a text analysis techniq

Question 5

Some customer segments do not adapt well to voice-guided technology-they instead prefer traditional person-to-person communications.

Accepted Answer

A) True 
 B)False

Question 6

Which of the following is a difference between structured and unstructured data?

Accepted Answer

A)  Structured data exists in predefined formats, whereas unstructured data needs to be converted before usage. 
B)  Structured data requires further processing before analysis, whereas unstructured data can be readily processed. 
C)  Structured data consists of images and videos, whereas unstructured data consists of numbers, locations and dates. 
D)  Structured data does not readily fit into a tabular format, whereas unstructured data is characterized by rows and columns. 
A)  Structured data exists in predefined formats, whereas unstructured data needs to be converted before usage. 
B)  Structured data requires further processing before analysis, whereas unstructured data can be readily processed. 
C)  Structured data consists of images and videos, whereas unstructured data consists of numbers, locations and dates. 
D)  Structured data does not readily fit into a tabular format, whereas unstructured data is characterized by rows and columns.

Question 7

According to the text, chatbots at ________ manage about 30 percent of the incoming volume, whereas the chatbots at ________ can manage almost 70 percent of customers' questions.

Accepted Answer

A)  Domino's; Hertz 
B)  Brand 24; Marriott 
C)  Dish Network; Avis 
D)  Hidden Valley; Clorox 
A)  Domino's; Hertz 
B)  Brand 24; Marriott 
C)  Dish Network; Avis 
D)  Hidden Valley; Clorox

Question 8

"The store looked fabulous, but not a single shirt fit me well." This sentence is an example of sentiment polarity.

Accepted Answer

A) True 
 B)False

Question 9

Identify an example of sentiment opposite polarity.

Accepted Answer

A)  "I could not buy the items I wanted as the shelves were empty." 
B)  "My pizza was delicious, and I loved the ambience of the restaurant." 
C)  "I enjoyed my coffee, but the barista was rude." 
D)  "I jogged for an hour today morning, and I feel awesome." 
A)  "I could not buy the items I wanted as the shelves were empty." 
B)  "My pizza was delicious, and I loved the ambience of the restaurant." 
C)  "I enjoyed my coffee, but the barista was rude." 
D)  "I jogged for an hour today morning, and I feel awesome."

Question 10

Structured data represents more than 75 percent of the data emerging from the internet and social media.

Accepted Answer

A) True 
 B)False

Question 11

Which of the following is an example of sentiment opposite polarity?

Accepted Answer

A)  "It rained all day today." 
B)  "My food arrived cold, and when I complained the server was impolite." 
C)  "Great coffee, great price, and friendly staff! Enjoyed the experience!" 
D)  "I woke up in a great mood today, but the hour-long commute ruined it." 
A)  "It rained all day today." 
B)  "My food arrived cold, and when I complained the server was impolite." 
C)  "Great coffee, great price, and friendly staff! Enjoyed the experience!" 
D)  "I woke up in a great mood today, but the hour-long commute ruined it."

Question 12

In text preprocessing, the term-document matrix consists of the x-axis that represents terms and the y-axis that represents the frequency of a particular term occurring.

Accepted Answer

A) True 
 B)False

Question 13

Which of the following is the first step of text analytics?

Accepted Answer

A)  text exploration 
B)  text acquisition and aggregation 
C)  text modeling 
D)  text preprocessing 
A)  text exploration 
B)  text acquisition and aggregation 
C)  text modeling 
D)  text preprocessing

Question 14

Term frequency measures the frequency of a term (or word) over all documents, whereas inverse document frequency (IDF) measures the number of times a term (or word) occurs in a document.

Accepted Answer

The answer of Term frequency measures the frequency of a...

Question 15

Identify a true statement about unstructured data.

Accepted Answer

A)  It requires further processing before it can be used for statistical methods. 
B)  It is made up of records that are organized in rows and columns. 
C)  This type of data can readily be stored in a database or spreadsheet format. 
D)  It is made up of predefined numbers, dates, and text strings. 
A)  It requires further processing before it can be used for statistical methods. 
B)  It is made up of records that are organized in rows and columns. 
C)  This type of data can readily be stored in a database or spreadsheet format. 
D)  It is made up of predefined numbers, dates, and text strings.

Question 16

Explain how a term-document matrix helps in identifying a bag of words to preprocess text.

Accepted Answer

A term-document matrix is a mathematical

Question 17

Explain natural language processing and how marketers can use it to their advantage.

Accepted Answer

Natural language processing (NLP) is a b

Question 18

For a specialty coffee company named Starcafe analyzing its online reviews, it is reasonable to categorize the words "Starcafe" and "coffee" as stop words.

Accepted Answer

A) True 
 B)False

Question 19

In which of the four steps of text analytics is a corpus of text data defined?

Accepted Answer

A)  text acquisition and aggregation 
B)  text modeling 
C)  text preprocessing 
D)  text exploration 
A)  text acquisition and aggregation 
B)  text modeling 
C)  text preprocessing 
D)  text exploration

Question 20

Identify and describe the steps of the Latent Dirichlet Allocation algorithm of text modeling.

Accepted Answer

Latent Dirichlet Allocation (LDA) is a p

A frequency bar chart technique counts the occurrence of words in a document while ignoring the order or the grammar of words.

Summarize practitioner Jasmine Jones's views about the potential for natural language processing in marketing.

In the preprocessing step of text analytics, ________ is the process of removing prefixes or suffixes from words to reduce them to their root form.

Explain the lemmatization technique of text analytics and provide several examples.

Some customer segments do not adapt well to voice-guided technology-they instead prefer traditional person-to-person communications.

Which of the following is a difference between structured and unstructured data?

According to the text, chatbots at manage about 30 percent of the incoming volume, whereas the chatbots at can manage almost 70 percent of customers' questions.

"The store looked fabulous, but not a single shirt fit me well." This sentence is an example of sentiment polarity.

Identify an example of sentiment opposite polarity.

Structured data represents more than 75 percent of the data emerging from the internet and social media.

Which of the following is an example of sentiment opposite polarity?

In text preprocessing, the term-document matrix consists of the x-axis that represents terms and the y-axis that represents the frequency of a particular term occurring.

Which of the following is the first step of text analytics?

Term frequency measures the frequency of a term (or word) over all documents, whereas inverse document frequency (IDF) measures the number of times a term (or word) occurs in a document.

Identify a true statement about unstructured data.

Explain how a term-document matrix helps in identifying a bag of words to preprocess text.

Explain natural language processing and how marketers can use it to their advantage.

For a specialty coffee company named Starcafe analyzing its online reviews, it is reasonable to categorize the words "Starcafe" and "coffee" as stop words.

In which of the four steps of text analytics is a corpus of text data defined?

Identify and describe the steps of the Latent Dirichlet Allocation algorithm of text modeling.

Introduction to Marketing Analytics

Data Management

Exploratory Data Analysis Using Cognitive Analytics

Data Visualization

Regression Analysis

Neural Networks

Automated Machine Learning

Cluster Analysis

Market Basket Analysis

Social Network Analysis

Web Analytics

Filters

Exam 10: Natural Language Processing - Text Mining and Sentiment Analysis

A frequency bar chart technique counts the occurrence of words in a document while ignoring the order or the grammar of words.

Summarize practitioner Jasmine Jones's views about the potential for natural language processing in marketing.

In the preprocessing step of text analytics, ________ is the process of removing prefixes or suffixes from words to reduce them to their root form.

Explain the lemmatization technique of text analytics and provide several examples.

Some customer segments do not adapt well to voice-guided technology-they instead prefer traditional person-to-person communications.

Which of the following is a difference between structured and unstructured data?

According to the text, chatbots at ________ manage about 30 percent of the incoming volume, whereas the chatbots at ________ can manage almost 70 percent of customers' questions.

"The store looked fabulous, but not a single shirt fit me well." This sentence is an example of sentiment polarity.

Identify an example of sentiment opposite polarity.

Structured data represents more than 75 percent of the data emerging from the internet and social media.

Which of the following is an example of sentiment opposite polarity?

In text preprocessing, the term-document matrix consists of the x-axis that represents terms and the y-axis that represents the frequency of a particular term occurring.

Which of the following is the first step of text analytics?

Term frequency measures the frequency of a term (or word) over all documents, whereas inverse document frequency (IDF) measures the number of times a term (or word) occurs in a document.

Identify a true statement about unstructured data.

Explain how a term-document matrix helps in identifying a bag of words to preprocess text.

Explain natural language processing and how marketers can use it to their advantage.

For a specialty coffee company named Starcafe analyzing its online reviews, it is reasonable to categorize the words "Starcafe" and "coffee" as stop words.

In which of the four steps of text analytics is a corpus of text data defined?

Identify and describe the steps of the Latent Dirichlet Allocation algorithm of text modeling.

Introduction to Marketing Analytics

Data Management

Exploratory Data Analysis Using Cognitive Analytics

Data Visualization

Regression Analysis

Neural Networks

Automated Machine Learning

Cluster Analysis

Market Basket Analysis

Social Network Analysis

Web Analytics

Filters

According to the text, chatbots at manage about 30 percent of the incoming volume, whereas the chatbots at can manage almost 70 percent of customers' questions.