Welcome, Guest: Register On Nairaland / LOGIN! / Trending / Recent / NewStats: 3,195,537 members, 7,958,653 topics. Date: Wednesday, 25 September 2024 at 07:47 PM |
Nairaland Forum / Nairaland / General / Education / Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander (637 Views)
Sentiment Analysis Python / A Nairalander Visits The World's Coolest Library In China, Shares Her Experience / A Nairalander Convocating At University Of Ibadan Today (pics) (2) (3) (4)
Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:03pm On Nov 06, 2017 |
Twitter sentiment analysis on Nigerian Telecommunication Networks. The task required in here is to know the sentiments( Opinion or emotional artificial intelligence) on Nigerian Telecom providers handle. I will be scraping tweets tweeted by users been directed to their ISPs ( Internet Service providers ) concerning issues they facing about a point in time. I am using the Nigerian network as case study it could work with some other areas too. Approach : Hybrid Naive Bayes approach ( Combination of Machine learning and Lexical dictionary ) Platform : Twitter Tool : R programming language ~ Often used by Data science students ( Could be done with Python too) Twitter Handles : Airtel - @airtel_care MTN - @MTN180 9mobile - @9mobilengcare Glo - @glocare Other areas sentiment analysis can used : Product and Service reviews Reputation Monitoring Result prediction Decision making etc Well, Enough of Hippie-Dippie side talk - Let get started ! CC: Seun , Lalasticlala |
Re: Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:03pm On Nov 06, 2017 |
Airtel Nigeria :https://imgur.com/a/vOUgY Picture 1 - Shows RAW data with users Tweets and Opinion :- Problem, Joy, Awkwardness, Negative feedback etc Picture 2 - Shows the cleaning up of data :- i.e Data Munging! Removing links and unneccessary junks that wouldn't add up to our final result.E.g Links ( / jdbdfb12 , @Handlename etc) Picture 3 - Visualization - After Categorizing every word to it group/class of sentiments we have the report below. Picture 4 : These are the words that makes up the visualization i.e WordCloud. The bigger it gets more often it gets used. |
Re: Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:03pm On Nov 06, 2017 |
MTN Nigeria: https://imgur.com/a/tp9tP Picture 1 - Shows RAW data with users Tweets and Opinion :- Problem, Joy, Awkwardness, Negative feedback etc Picture 2 - Shows the cleaning up of data :- i.e Data Munging! Removing links and unneccessary junks that wouldn't add up to our final result. Picture 3 - Visualization - After Categorizing every word to it group/class of sentiments we have the report above. Picture 4 : These are the words that makes up the visualization i.e WordCloud. The bigger it gets more often it gets used. |
Re: Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:04pm On Nov 06, 2017 |
9mobile Nigeria: https://imgur.com/a/43Yr8 Picture 1 - Shows RAW data with users Tweets and Opinion :- Problem, Joy, Awkwardness, Negative feedback etc Picture 2 - Shows the cleaning up of data :- i.e Data Munging! Removing links and unneccessary junks that wouldn't add up to our final result. Picture 3 - Visualization - After Categorizing every word to it group/class of sentiments we have the report above. Picture 4 : These are the words that makes up the visualization i.e WordCloud. The bigger it gets more often it gets used. |
Re: Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:04pm On Nov 06, 2017 |
Glo Nigeria: https://imgur.com/a/e0Y46 Picture 1 - Shows RAW data with users Tweets and Opinion :- Problem, Joy, Awkwardness, Negative feedback etc Picture 2 - Shows the cleaning up of data :- i.e Data Munging! Removing links and unneccessary junks that wouldn't add up to our final result. Picture 3 - Visualization - After Categorizing every word to it group/class of sentiments we have the report above. Picture 4 : These are the words that makes up the visualization i.e WordCloud. The bigger it gets more often it gets used. |
Re: Twitter Sentiment Analysis On Nigerian Telecom. Networks By A Nairalander by Tolzeal(m): 12:04pm On Nov 06, 2017 |
Thanks all. Based on the report one good deduce the best network when seeking to pick up a network provider for your home use. It will also help the Network provider to help fix problems areas where users are lamenting. I hope it helps |
(1) (Reply)
I Need Your Advise, PLEASE / Government Technical College, Osogbo 2nd Annual Inter-house Sport Competition / Federal University Otuoke Bayelsa 2017/2018 Admission List Is Out(merit List)
(Go Up)
Sections: politics (1) business autos (1) jobs (1) career education (1) romance computers phones travel sports fashion health religion celebs tv-movies music-radio literature webmasters programming techmarket Links: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Nairaland - Copyright © 2005 - 2024 Oluwaseun Osewa. All rights reserved. See How To Advertise. 19 |