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Table 7 Examples of misclassifications

From: Deep learning for pollen allergy surveillance from twitter in Australia

No

Example

Prediction

Prob.

Actual

P 1

With this hay fever making me feel like I don’t have enough air in my lungs I hope this helps;-)

2 Informative - generic

0.509

1 Informative - symptom

 

Explanation: Rare expression of the symptom, referring to breathing difficulty, and negation ocurrence. Still, the low predictive probability obtained.

   

P 2

How can I be awake with hay fever at 2am?!

2 Informative - generic

0.543

1 Informative - symptom

 

Explanation: Short length and expressiveness indicators (’?!’) typical for generic class 2. Still, the low predictive probability obtained.

   

P 3

@username Same!!! Grass gives me bad rashes and hay fever as well as pollen and it sucksss

2 Informative - generic

0.993

1 Informative - symptom

 

Explanation: Repeated characters for added emphasis and expressiveness (’!!!’) typical for generic class 2. New and rare symptom occurred.

   

P 4

Dubliner Goran Pavlovic claims started stinging himself with nettles and his hay fever symptoms started to disappear, if suffered would give it a try

1 Informative - treatment

0.527

3 Non-Informative - news

 

Explanation: Identified as treatment. The news content is paraphrased by the user, thus classified as personal. Still, the low predictive probability obtained.

   

P 5

Could be a dangerous day tomorrow for asthmatic and hay fever sufferers. If we were in summer and not winter we would be looking at a severe fire danger. Those are warm winds.

2 Informative - generic

0.863

3 Non-Informative - warning

 

Explanation: Warning content paraphrased by the user - no typical ’warning’/’be careful’ phrase identified.

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