Please use this identifier to cite or link to this item:
http://10.1.7.192:80/jspui/handle/123456789/7607
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jadeja, Gayatriba | - |
dc.date.accessioned | 2017-07-26T06:19:03Z | - |
dc.date.available | 2017-07-26T06:19:03Z | - |
dc.date.issued | 2017-05 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/7607 | - |
dc.description.abstract | Sarcasm is a sharp remark to mock or insult using words which means the opposite of what is literally said. Sarcasm is extremely healthy for the mind. People who understand sarcasm well are often good at reading peoples mind. Sarcasm is very tricky part of speech and is relatively unexplored for social media analysis. It being tricky is very hard to detect not just automatically but even for humans. Sarcasm is a distinct kind of sentiment in which the meaning of the statement is opposite of what is said i.e the literal meaning of the statement is opposite of actual meaning. It is used mostly to mock or insult people or to be funny. It is expressed though body gestures, tonal changes but for obvious reason they cannot be documented and hence not useful for sarcasm detection in text. Our goal is to develop a system for sarcasm detection.By using interjection words sarcasm can be detected. Select interjection words from the statement and their reply and based on that sarcasm detection is done . If the statement has negative sentiment and its reply has interjection word followed by positive sentiment sentence or vice-verse then it is considered sarcastic. | en_US |
dc.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 15MCEI08; | - |
dc.subject | Computer 2017 | en_US |
dc.subject | Project Report 2017 | en_US |
dc.subject | Computer Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 15MCEI | en_US |
dc.subject | 15MCEI08 | en_US |
dc.subject | INS | en_US |
dc.subject | INS 2017 | en_US |
dc.subject | CE (INS) | en_US |
dc.title | Sarcasm Detection | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, CE (INS) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
15MCEI08.pdf | 15MCEI08 | 763.87 kB | Adobe PDF | ![]() View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.