dc.contributor.author |
Thu, Pyae Phyo
|
|
dc.contributor.author |
Nwe, Nwe
|
|
dc.date.accessioned |
2019-07-11T03:58:24Z |
|
dc.date.available |
2019-07-11T03:58:24Z |
|
dc.date.issued |
2017-02-16 |
|
dc.identifier.uri |
http://onlineresource.ucsy.edu.mm/handle/123456789/702 |
|
dc.description.abstract |
Ever escalating usage of social media brings as
a powerful communication and information sharing
tool used by millions of people around the world to
post how they feel and what is happening now. It turn
into a potential source of crowd wisdom extraction
especially in terms of sentiments analysis and opinion
mining which lead to a significant task of current
research area. Major challenges in this area is to tame
the data in terms of noise, relevance, emoticons,
folksonomies and slangs. TwitPre offer a regular
expression based preprocessing tasks on tweets.
Expressions are defined according to the outcomes of
elegant analysis on twitter data. Experiments were
carried out to observe the effect of proposed tool which
clearly indicates the improvements in accuracy
compared with the existing baseline. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Fifteenth International Conference on Computer Applications(ICCA 2017) |
en_US |
dc.subject |
Social Media Analysis |
en_US |
dc.subject |
Tweets Preprocessing Tool |
en_US |
dc.title |
TwitPre: Tweets Preprocessing Tool for Social Media Analysis |
en_US |
dc.type |
Article |
en_US |