Entity based sentiment analysis of electronic news (Record no. 65861)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01456nam a22001217a 4500 |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Zahid Hussain |
| -- | 12MSIT19 |
| -- | Supervisor - Dr. Shah Zaman Nizamani |
| 245 ## - TITLE STATEMENT | |
| Title | Entity based sentiment analysis of electronic news |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Nawabshah: |
| Name of publisher | QUEST, |
| Year of publication | 2019. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 37p. |
| 500 ## - GENERAL NOTE | |
| General note | ABSTRACT<br/><br/>News articles and electronic media provide us massive unstructured bulk information about day by day events. Every day millions of news and articles are published in newspapers. The news and articles give some information regarding physical or virtual entities. In the news or articles three categories of views are given. The view may be positive, negative or neutral. The view portrays by the news or articles is important for improving the performance of an entity. The aim of this research is to find the entity based sentiment analysis of the news. With the help of sentiment analysis polarity (Positive. Negative. Neutral) of any entity can be get. For this research a data crawler tool is developed in java language and sentiment analysis is done by using Stanford CoreNLP. For testing purpose the articles for taken from website of dawn newspaper. For sample data, news were downloaded continuously for seven weeks regarding some entities.<br/><br/>Keywords: Entity Based Sentiment Analysis, NLP (Natural Language Processing) Data Crawling, Electronic News articles, Stanford CoreNLP . |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Department of Information Technology |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Thesis and Dissertation |
| Withdrawn status | Lost status | Home library | Current library | Date acquired | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|---|---|
| Central Library, QUEST, Nawabshah | Research Section | 15/10/2019 | R/IMS-19 | MP/53-652 | Thesis and Dissertation |