Welcome to Twitter Sentiment Analysis AI Challenge!

The aim of the challenge is to classify tweets into 3 categories namely "positive", "negative" and "neutral". The dataset contains 3 files:

• TRAIN.csv (contains training data)
• TEST.csv (data for prediction)
• SampleSubmission.csv

The TRAIN.csv file consists of 15 attributes

• tweet_id
• airline_sentiment (Target column for prediction)
• airline_sentiment_confidence
• negativereason
• negativereason_confidence
• airline
• airline_sentiment_gold
• name
• negativereason_gold
• retweet_count
• text
• tweet_coord
• tweet_created
• tweet_location
• user_timezone

Please refer to the Submission Guidelines for the final format of the submission.

The final submission must include:

output.csv (single file having results for "TEST.csv")

The first row should correspond to the column names:

• Index (Row Index of TEST.csv)
• Sentiment (Target Attribute)

NOTE: This dataset contains lot of missing values and inconsistent formatting, so participants will have to per-process the data before training.

Sample Output:

...

How to make a submission?

1. Click on "My Submission"
2. On the next page, click on "+ New Submission"
3. Upload your CSV in the next page and click on "Submit for Review"

Please note:

1. You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
2. Your submission will be auto graded and you will be able to see your results instantly.
3. If there is any error in the submission, your final score will be marked as 0 or a warning prompt of “Invalid Score” will be displayed.

Judgement

1. Accuracy Score

Rules

1. The submission should be in a proper format as described by "Submission Guidelines".
2. Late submission will not be accepted beyond provided deadline (Indian Standard Time).

NOTE: We may request for the code files if there is any discrepancy in your score. Your score will be marked invalid if the request for code is not fulfilled by you.

Rewards

1. Top three participants will get a place in Hall of Fame page.