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Hello: I've been using your package to get the sentiment of tweets. It's been working very well, so thank you!
Recently, the data source I use to retrieve tweets has started providing the full text of tweets, instead of a truncated version when the tweets are long. (Some tweets are very, very long.)
Not knowing better, I continued to analyze tweet sentiment as before, but I started getting tensorflow warning messages about using more than 10% of memory. After these messages, the model would just stall and never finish the job.
I tried running the sentiment_score() function on smaller batches of tweets and that worked for a few batches, but then the problem arose again for a single small batch.
I knew the number of tweets definitely wasn't the problem -- I was only doing 100 at a time -- so I figured the length of the text must be the issue. I added a step to truncate tweets to 400 characters and that completely solved the problem.
My suggestion would be to add a warning about the length of the text affecting the performance in the Troubleshooting section of the page.
The text was updated successfully, but these errors were encountered:
Hello: I've been using your package to get the sentiment of tweets. It's been working very well, so thank you!
Recently, the data source I use to retrieve tweets has started providing the full text of tweets, instead of a truncated version when the tweets are long. (Some tweets are very, very long.)
Not knowing better, I continued to analyze tweet sentiment as before, but I started getting tensorflow warning messages about using more than 10% of memory. After these messages, the model would just stall and never finish the job.
I tried running the sentiment_score() function on smaller batches of tweets and that worked for a few batches, but then the problem arose again for a single small batch.
I knew the number of tweets definitely wasn't the problem -- I was only doing 100 at a time -- so I figured the length of the text must be the issue. I added a step to truncate tweets to 400 characters and that completely solved the problem.
My suggestion would be to add a warning about the length of the text affecting the performance in the Troubleshooting section of the page.
The text was updated successfully, but these errors were encountered: