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https://issues.apache.org/jira/browse/TIKA-2016?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15992294#comment-15992294
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ASF GitHub Bot commented on TIKA-2016:
--------------------------------------
thammegowda commented on issue #169: TIKA-2016 Sentiment Analysis Parser
Contributed by amensiko and thammegowda
URL: https://github.com/apache/tika/pull/169#issuecomment-298491221
I thought no further action needed on this PR (looks like I missed
something, sorry!)
If it is about the categorical analysis, there are no code changes needed.
Just use this config for `--config=` argument above.
```xml
<properties>
<parsers>
<parser
class="org.apache.tika.parser.sentiment.analysis.SentimentParser">
<mime>text/plain</mime>
<mime>application/sentiment</mime>
<params>
<!--This is default <param name="modelPath"
type="string">https://raw.githubusercontent.com/USCDataScience/SentimentAnalysisParser/master/sentiment-models/en-netflix-sentiment.bin</param>
-->
<param name="modelPath"
type="string">https://raw.githubusercontent.com/USCDataScience/SentimentAnalysisParser/master/sentiment-models/ht-sentiment-categ.bin</param>
<!--This can also be relative path
sentiment-models/en-stanford-sentiment.bin-->
</params>
</parser>
</parsers>
</properties>
```
I tested again now, it worked!
- Users are free to point to any opennlp classifier model they wish to.
- The `modelPath` can be HTTP URL or local file path or relative path to the
classloader.
I thought I handled all the cases with our awesome XML parameter binding
feature.
What did I miss?
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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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