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

Cyberbullying or Online harassment detection on social media for variousmajor languages is currently being given a good amount of focus by researchersworldwide. Being the seventh most speaking language in the world and increasingusage of online platform among the Bengali speaking people urge to findeffective detection technique to handle the online harassment. In this paper,we have proposed binary and multiclass classification model using hybrid neuralnetwork for bully expression detection in Bengali language. We have used 44,001users comments from popular public Facebook pages, which fall into five classes- Non-bully, Sexual, Threat, Troll and Religious. We have examined theperformance of our proposed models from different perspective. Our binaryclassification model gives 87.91% accuracy, whereas introducing ensembletechnique after neural network for multiclass classification, we got 85%accuracy.

Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language