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

Social media has become a major driver of social change, by facilitating theformation of online social movements. Automatically understanding theperspectives driving the movement and the voices opposing it, is a challengingtask as annotated data is difficult to obtain. We propose a weakly supervisedgraph-based approach that explicitly models perspectives in#BackLivesMatter-related tweets. Our proposed approach utilizes asocial-linguistic representation of the data. We convert the text to a graph bybreaking it into structured elements and connect it with the social network ofauthors, then structured prediction is done over the elements for identifyingperspectives. Our approach uses a small seed set of labeled examples. Weexperiment with large language models for generating artificial trainingexamples, compare them to manual annotation, and find that it achievescomparable performance. We perform quantitative and qualitative analyses usinga human-annotated test set. Our model outperforms multitask baselines by alarge margin, successfully characterizing the perspectives supporting andopposing #BLM.

"A Tale of Two Movements": Identifying and Comparing Perspectives in  #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly  Supervised Graph-based Structured Prediction