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https://issues.apache.org/jira/browse/TIKA-2016?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15968806#comment-15968806
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ASF GitHub Bot commented on TIKA-2016:
--------------------------------------
thammegowda opened a new pull request #169: TIKA-2016 Sentiment Analysis
Parser Contributed by amensiko and thammegowda
URL: https://github.com/apache/tika/pull/169
This PR is a refresh of work started by @amensiko and left unmerged in #127
What is supported:
- Sentiment Analysis is powered by OpenNLP
- Model path can be changed to any compatible Open NLP Max Ent model ( to
change, update tika config xml)
- It can be HTTP URL (caching is not supported at the moment, use it for
testing only)
- It can be a file known to class loader (for hadoop /spark users)
- It can be a file on file system (for stand alone users)
- by default, it retrieves a model from USC DataScience's github repo,
trained on netflix dataset of positive negative sentiments
**Test case included?** yes - Checkout SentimentParserTest
**Example Tika Conf included?** yes - checkout the config file used by the
test case.
## How to test?
```bash
$ mvn clean package
$ echo "What a wonderful thought it is that some of the best days of our
lives havent happened yet" > test.sent
$ java -jar tika-app/target/tika-app-1.15-SNAPSHOT.jar \
--config=tika-parsers/src/test/resources/org/apache/tika/parser/sentiment/analysis/tika-config-sentiment-opennlp.xml
\
-m test.sent
# Output
Content-Length: 91
Content-Type: application/sentiment
Sentiment: positive
X-Parsed-By: org.apache.tika.parser.CompositeParser
X-Parsed-By: org.apache.tika.parser.sentiment.analysis.SentimentParser
resourceName: test.sent
```
Note: `Sentiment: positive` was added to metadata
#Closes #127 and TIKA-2016
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> A parser that combines Apache OpenNLP and Apache Tika and provides facilities
> for automatically deriving sentiment from text.
> -----------------------------------------------------------------------------------------------------------------------------
>
> Key: TIKA-2016
> URL: https://issues.apache.org/jira/browse/TIKA-2016
> Project: Tika
> Issue Type: New Feature
> Components: parser
> Reporter: Anastasija Mensikova
> Assignee: Chris A. Mattmann
> Labels: analysis, gsoc2016, memex, parser, sentiment
> Fix For: 1.15
>
>
> A new project that implements a parser that uses Apache OpenNLP and Apache
> Tika to perform Sentiment Analysis.
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