IDENTIFICATION OF CERTAIN EMOTIONS IN TEXTIDENTIFICATION OF CERTAIN EMOTIONS IN TEXT(NATURAL LANGUAGE PROCESSING)

Mentor: Mentor: Prof. Amitabha MukherjeeProf. Amitabha Mukherjee

Pranjal Singh 10511 spranjal@iitk.ac.inDivyanshu Bhartiya 10250 divbhar@iitk.ac.in

CS365: ARTIFICIAL INTELLIGENCE

04/21/23 1

IMPORTANCE + SCOPEIMPORTANCE + SCOPE

04/21/23 2

METHODOLOGY: OVERVIEWMETHODOLOGY: OVERVIEW

04/21/23 3

SUPERVISED LEARNINGSUPERVISED LEARNINGPCFG parser result : “He might have lung cancer . It s just a

rumor ... but it makes sense . He is very depressed and that s just the beginning of things”

<type> negative </type>

<score> -0.357542 </score

Sentiment Analysis Result:

04/21/23 4

UNSUPERVISED LEARNINGUNSUPERVISED LEARNING

“He might have lung cancer . It s just a rumor ... but it makes sense . He is very depressed and that s just the beginning of things”

Emotion Probability

Sad 1.00000000e+000

Fear 1.24334077e-086

Joy 0.00000000e+000

Guilt 0.00000000e+000

Shame 0.00000000e+000

Anger 7.25160223e-034

Disgust 1.27906894e-132

04/21/23 5

PLSA PLSA

04/21/23 6

PLSA aims to discover something about the meaning behind the words; about the topics in the documents

SAMPLE RESULT:SAMPLE RESULT:

04/21/23 7

DIFFERENCE IN OUR APPROACH

Use of PLSA instead of LSA which “Carlos Strapparava” and “Rada Mihalcea” have done in their work.

Instead of annotated corpus which is used by “Carlos Strapparava” and “Rada Mihalcea” for applying LSA we are updating the term document matrix for later use of PLSA.

Removal of certain words that don’t contribute to emotions.

04/21/23 8