English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Bangla is the 7th most widely spoken language globally, with a staggering 234million native speakers primarily hailing from India and Bangladesh. Thismorphologically rich language boasts a rich literary tradition, encompassingdiverse dialects and language-specific challenges. Despite its linguisticrichness and history, Bangla remains categorized as a low-resource languagewithin the natural language processing (NLP) and speech community. This paperpresents our submission to Task 2 (Sentiment Analysis of Bangla Social MediaPosts) of the BLP Workshop. We experiment with various Transformer-basedarchitectures to solve this task. Our quantitative results show that transferlearning really helps in better learning of the models in this low-resourcelanguage scenario. This becomes evident when we further finetune a model whichhas already been finetuned on twitter data for sentiment analysis task and thatfinetuned model performs the best among all other models. We also perform adetailed error analysis where we find some instances where ground truth labelsneed to be relooked at. We obtain a micro-F1 of 67.02\% on the test set and ourperformance in this shared task is ranked at 21 in the leaderboard.

BanglaNLP at BLP-2023 Task 2: Benchmarking different Transformer Models for Sentiment Analysis of Bangla Social Media Posts