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    961 aylien sentiment analysis jobs found, pricing in USD

    I would like to finish my project within a month: The project involves a hybrid method for sentiment analyiss of tweets written in Turkish language: There are 2 ways in any of whom a kind of machine learning approach had to be applied. For better communication my phone#: 00905346967077 A simple solution is below,but it relies heavily on NLTK library

    $178 (Avg Bid)
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    6 bids

    Validate sentiment and concept to make sure that the information detected by the system is accurate. more details to be provided to the person awarded

    $163 (Avg Bid)
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    8 bids

    Validate sentiment and concept to make sure that the information detected by the system is accurate. more details to be provided to the person awarded.

    $1168 (Avg Bid)
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    17 bids

    ...every time a tweet is captured and stored in database. Part 3. 1. Do sentiment analysis of the tweet text stored in database and flag it as being either: Positive, Neutral or Negative Part 4. 1. Count number of times a keyword was mentioned daily 2. Count number of sentiment mentions (ie. how many negative, positive and neutral mentions per day

    $157 (Avg Bid)
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    15 bids

    Requirement is to collect data from different blogs on a particular topic, do "Topic Modelling" and " Sentiment Analysis" meaning filter out if people have positive,negative or neutral emotions towards that topic.

    $374 (Avg Bid)
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    13 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $11 / hr (Avg Bid)
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    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $10 / hr (Avg Bid)
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    20 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $15 / hr (Avg Bid)
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    7 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $9 / hr (Avg Bid)
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    6 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $10 / hr (Avg Bid)
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    5 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $16 / hr (Avg Bid)
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    6 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $171 (Avg Bid)
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    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $153 (Avg Bid)
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    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $219 (Avg Bid)
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    7 bids

    ... * Sentiment precision: you will have to validate the sentiment detected by the system (positive/negative/neutral) from 1000 mentions (short snippets of text of around 6 words). NOTE: In order to ensure the expected quality of the files, the accepted margin of error of the Sentiment precision file is of around 5% based on previous analysis. The

    $167 (Avg Bid)
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    -You have to apply Machine learning here, by combining multiple method of it. -Music will be our task. Based on a person taste in music, we can judge his behavioral feature at present. -You have to take data sets and plot in the end. Describing the performance of the method. -And it will be very helpful for me if you give me step by step procedure that you have been following in order to comple...

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    Hi, I have an algorithm to carry out the sentiment analysis for news and blogs. I want it to get implement.

    $171 (Avg Bid)
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    Looking to build a predictive model of the stock / currency market using Deep Learning models, specific (limited) sentiment data possibly an ensemble approach coupled with time series data & several other avenues to discuss in more detail. Duration for project would be at least 2 months on going work which would be extended upon review.

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    I've got some tweets which have been scored to show if they are positive or negative. But now I want them sorted so I can analyse the bad tweets and good tweets separately. I plan on analysing the bad/good tweets with word clouds and checking for word frequencies. I need someone to sort them for me so I can do this. So a very mini project, hoping for it to be completed no later than Saturd...

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    it is a project for sentiment analysis using some algorithm written in Jupyter

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