Title : Multi lingual and code mixed based Approaches for sentiment analysis Using twitter data

Type of Material: Thesis
Title: Multi lingual and code mixed based Approaches for sentiment analysis Using twitter data
Researcher: ARUN KODIREKKA
Guide: A. SRINAGESH
Department: Department of Computer Science and Engineering
Publisher: Acharya Nagarjuna University, Guntur
Place: Guntur
Year: 2024
Language: English
Subject: Computer Science
Computer Science Software Engineering
Engineering and Technology
Computer Science and Information Technology
Engineering and Technology
Dissertation/Thesis Note: PhD; Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Guntur; 2024; Y16CSER001
Fulltext: Shodhganga

00000000ntm a2200000ua 4500
001455007
003IN-AhILN
0052024-09-20 15:33:54
008__240920t2024||||ii#||||g|m||||||||||eng||
035__|a(IN-AhILN)th_455007
040__|aNGJN_522510|dIN-AhILN
041__|aeng
100__|aARUN KODIREKKA|eResearcher
110__|aDepartment of Computer Science and Engineering|bAcharya Nagarjuna University, Guntur|dGuntur|ein|0U-0003
245__|aMulti lingual and code mixed based Approaches for sentiment analysis Using twitter data
260__|aGuntur|bAcharya Nagarjuna University, Guntur|c2024
300__|dCD
502__|cDepartment of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Guntur|d2024|oY16CSER001|bPhD
518__|d2024|oDate of Award
518__|oDate of Registration|d2016
650__|aComputer Science and Information Technology|2UGC
650__|aEngineering and Technology|2AIU
653__|aComputer Science
653__|aComputer Science Software Engineering
653__|aEngineering and Technology
700__|aA. SRINAGESH|eGuide
856__|uhttp://shodhganga.inflibnet.ac.in/handle/10603/559136|yShodhganga
905__|afromsg

User Feedback Comes Under This section.