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enesgerem/airline-sentiment-models

sourceHugging Facecc-by-nc-sa-4.0updated 4mo agoView on Hugging Face

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Airline Passenger Sentiment Models

Fine-tuned transformer checkpoints from the M.Sc. thesis "Multi-Source Natural Language Processing for Airline Passenger Sentiment and Satisfaction Analysis" (Enes Gerem, Hacettepe University).

Each checkpoint is a 3-class sentiment classifier (negative / neutral / positive) fine-tuned on one of seven source configurations drawn from Twitter, Skytrax, and TripAdvisor airline feedback.

Label mapping

id	label
0	negative
1	neutral
2	positive

Available checkpoints (subfolders)

Family	Source config	Subfolder
BERT-base	`twitter`	`bert/twitter`
BERT-base	`skytrax`	`bert/skytrax`
BERT-base	`tripadvisor`	`bert/tripadvisor`
BERT-base	`twitter+skytrax`	`bert/twitter+skytrax`
BERT-base	`twitter+tripadvisor`	`bert/twitter+tripadvisor`
BERT-base	`skytrax+tripadvisor`	`bert/skytrax+tripadvisor`
BERT-base	`twitter+skytrax+tripadvisor`	`bert/twitter+skytrax+tripadvisor`
RoBERTa-base	`twitter`	`roberta/twitter`
RoBERTa-base	`skytrax`	`roberta/skytrax`
RoBERTa-base	`tripadvisor`	`roberta/tripadvisor`
RoBERTa-base	`twitter+skytrax`	`roberta/twitter+skytrax`
RoBERTa-base	`twitter+tripadvisor`	`roberta/twitter+tripadvisor`
RoBERTa-base	`skytrax+tripadvisor`	`roberta/skytrax+tripadvisor`
RoBERTa-base	`twitter+skytrax+tripadvisor`	`roberta/twitter+skytrax+tripadvisor`
DistilBERT-base	`twitter`	`distilbert/twitter`
DistilBERT-base	`skytrax`	`distilbert/skytrax`
DistilBERT-base	`tripadvisor`	`distilbert/tripadvisor`
DistilBERT-base	`twitter+skytrax`	`distilbert/twitter+skytrax`
DistilBERT-base	`twitter+tripadvisor`	`distilbert/twitter+tripadvisor`
DistilBERT-base	`skytrax+tripadvisor`	`distilbert/skytrax+tripadvisor`
DistilBERT-base	`twitter+skytrax+tripadvisor`	`distilbert/twitter+skytrax+tripadvisor`

Usage

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification

repo = "enesgerem/airline-sentiment-models"
subfolder = "roberta/twitter"   # pick any subfolder from the table above

tokenizer = AutoTokenizer.from_pretrained(repo, subfolder=subfolder)
model = AutoModelForSequenceClassification.from_pretrained(repo, subfolder=subfolder)

Citation / data

Datasets are used for non-commercial academic research. The Twitter component is the Crowdflower US Airline Sentiment benchmark (CC BY-NC-SA); the Skytrax and TripAdvisor components are point-in-time scrapes of publicly available review pages, used under each platform's terms of service.