Name
Abstract | ||
|---|---|---|
In this paper, we discuss a variety of issues related to opinion mining from microposts, and the challenges they impose on an NLP system, along with an example application we have developed to determine political leanings from a set of pre-election tweets. While there are a number of sentiment analysis tools available which summarise positive, negative and neutral tweets about a given keyword or topic, these tools generally produce poor results, and operate in a fairly simplistic way, using only the presence of certain positive and negative adjectives as indicators, or simple learning techniques which do not work well on short microposts. On the other hand, intelligent tools which work well on movie and customer reviews cannot be used on microposts due to their brevity and lack of context. Our methods make use of a variety of sophisticated NLP techniques in order to extract more meaningful and higher quality opinions, and incorporate extra-linguistic contextual information. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-25953-1_8 | ESWC Workshops |
Keywords | DocType | Volume |
intelligent tool,automatic detection,short microposts,opinion mining,higher quality opinion,sophisticated nlp technique,example application,neutral tweet,negative adjective,political opinion,extra-linguistic contextual information,nlp system,nlp | Conference | 7117 |
ISSN | Citations | PageRank |
0302-9743 | 45 | 1.40 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diana Maynard | 1 | 1799 | 160.95 |
| Adam Funk | 2 | 314 | 17.90 |