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R-Shief Semantic Analytics of 2011 Pan-Arab Revolutions from VJ Um Amel on Vimeo.

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  #1
Administrator

18-05-11

 
Laila's Avatar

Semantic Web Analysis of Big Data in Arabic, French, and English


Project Information

Maintenance status: Early Development
Development Status: Under Active Development
Project Versions: 2.0
Project in development since: February 2011



Description

USC’s Annenberg Innovation Lab has hired R-Shief Project Lead Laila Shereen Sakr as a research assistant to work with IBM’s LanguageWare tools in order to extend their semantic content analysis into Arabic and French.

This project led by USC's Annenberg Innovation Lab is producing a set of Semantic Analyses on the 2011 Arab Spring by creating a data model that will provide lexical analyses for Arabic-only sites, English-only sites, and Arabic-English sites based on language specific set of rules and dictionaries that are applied. This will enable the Annenberg Innovation Lab and R-Shief to perform significant semantic content analysis on Arabic language on the web.

Using R-Shief’s Twitter hashtag archive, Sakr has determined that the majority of tweets are in Arabic. Without being able to pre-process Arabic language content in its native language, sentiment and semantic analyses cannot be properly performed. Rather, users will only be able to provide the usual content analyses on not-so-usual material. Our collaborative sentiment and semantic analyses will be a great contribution to the scholars, artists and journalists using R-Shief's Twitter data. The end result will be a series of visualizations and extensive semantic analysis of the rapidly unfolding current events in the Middle East.
 

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  #2
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17-07-11

 
badr42's Avatar
Re: Semantic Web Analysis of Big Data in Arabic, French, and English

I've been researching arabic sentiment analysis for short sentences for a while now, there are several libraries that can handle english to a certain extent however so far the only software capable of analyzing Arabic messages is owned by IBM as a part of their online reputation analysis tool, and they aren't even selling it just yet as it is still in the development phase.

I've been trying to find a work around using google translate however the quality of the translated takes rarely manages to carry over the emotion contained in the original message.

anyway i'm interested and i'd like you to check what i've been working on so far, using stock enterprise monitoring tool to monitor the frequency of usage of certain hashtags on twitter and plotting the results.

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  #3
Administrator

18-07-11

 
Laila's Avatar
Re: Semantic Web Analysis of Big Data in Arabic, French, and English

Quote:
Originally Posted by badr42 View Post
I've been researching arabic sentiment analysis for short sentences for a while now, there are several libraries that can handle english to a certain extent however so far the only software capable of analyzing Arabic messages is owned by IBM as a part of their online reputation analysis tool, and they aren't even selling it just yet as it is still in the development phase.

I've been trying to find a work around using google translate however the quality of the translated takes rarely manages to carry over the emotion contained in the original message.

anyway i'm interested and i'd like you to check what i've been working on so far, using stock enterprise monitoring tool to monitor the frequency of usage of certain hashtags on twitter and plotting the results.

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thanks for your input. i think you are right. there is a current lack in the for open source natural language programming in arabic. and ibm has a hold of the market. i think the work you are doing is very interesting. i would like to invite you to post some of your data visuals and work on r-shief. let's chat.
 

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  #4
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12-12-11

 
jackcurtis's Avatar
Re: Semantic Web Analysis of Big Data in Arabic, French, and English

"The end result will be a series of visualizations and extensive semantic analysis of the rapidly unfolding current events in the Middle East." -- as seen by the participants, I guess.
 

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