SBL1400 Lecture 2 Quiz – Text & Sentiment Analysis
Authored by Shahid Jilani
Business
1st Grade
Used 3+ times
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15 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What makes unstructured data such as text, audio, and video harder to analyze than structured data?
It lacks visual components
It changes in real-time
It cannot be directly stored in tabular rows and columns
It is typically free from noise
2.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which elements are essential when preprocessing textual data before analysis? Select all that apply.
Tokenisation
Lowercasing text
Removing punctuation
Converting to audio
Stemming
3.
FILL IN THE BLANKS QUESTION
1 min • 1 pt
The process of reducing words to their root forms in order to treat similar words as one is known as (a) .
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Tokenisation is the process of mapping text documents into rows and columns for numerical analysis.
Answer explanation
Explanation: That describes the term-document matrix; tokenisation splits text into individual terms.
5.
MATCH QUESTION
1 min • 1 pt
Match each concept to its most appropriate definition:
Numerical representation of emotional to
Sentiment Score
Contextual Interpretation
Contextual Interpretation
Table showing presence/absence of terms
Term-Document Matrix
Collection of text documents
Corpus
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A text analyzer identifies the sentence "My delayed flight was absolutely amazing!" as positive. What is the likely cause of this misinterpretation?
Lack of punctuation
Presence of ambiguous vocabulary
Sarcasm misclassified as genuine sentiment
Irrelevant tokens
7.
DRAG AND DROP QUESTION
1 min • 1 pt
Arrange the following preprocessing steps in logical order for text mining: (a) (b) (c) (d)
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