dc.contributor.author |
DR SHOAB A KHAN, BURHAN,TAHA,QALAB-E-ABBAS,SAMEED |
|
dc.date.accessioned |
2025-04-29T04:02:40Z |
|
dc.date.available |
2025-04-29T04:02:40Z |
|
dc.date.issued |
2014 |
|
dc.identifier.other |
DE-COMP-32 |
|
dc.identifier.uri |
http://10.250.8.41:8080/xmlui/handle/123456789/52588 |
|
dc.description |
SUPERVISOR
Dr Shoab A Khan
Dr Usman Qamar |
en_US |
dc.description.abstract |
In the world of today media is one of the strongest tools in the domain of psychological
warfare.Unfortunately now a days, Pakistan in not in the good books of media, which if
affecting our tourism, trade and many other factors that contribute in the development of a
country. We are introducing a solution for policy makers so that they can analyze Pakistan’s
perception in the media with concrete statistics that will be provided to them by this tool. So,
that they could take all possible measures to counter these problems. Our algorithm makes it
easy to analyze news from various sources and uses graphical as well as geographical
representations to help the user better understand the situation.
The online news are best resource to get the latest and fastest information around the globe.
So, we will crawl the web and gather news from newspapers of various countries such as
India (The Hindu), United States (Seattle Times) and Pakistan (The News).The biggest issue
with online news articles is that they are unstructured, so after collection of these articles they
have to go through massive processing to turn them into a structured form so that the
consistency of the database is maintained. After structuring the data we apply Natural
Language Processing algorithms to first tag the parts of speech in the news article and then
apply sentiment analysis on these parts speech to calculate positive sentiment, negative
sentiment and objectivity. The data set then goes through further processing to tag the
emotions represented in the particular news. Once all the processing is complete we make
use of different graphical representation to help the user understand the facts and statistics
more accurately. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
College of Electrical & Mechanical Engineering (CEME), NUST |
en_US |
dc.title |
MEDIA PERCEPTION INDICATOR |
en_US |
dc.type |
Project Report |
en_US |