Published October 21, 2024 | Version v1
Journal article Open

BioMAISx: A Corpus for Aspect-Based Sentiment Analysis of Media Representations of Agricultural Biotechnologies in Africa

  • 1. University of Chicago
  • 2. Stony Brook University
  • 3. University of San Francisco

Description

News articles constitute a valuable resource for opinion mining, as they contain important perspectives related to the subject matter they cover. In this paper, we explore how aspect-based sentiment analysis might help in understanding the public discourse surrounding agricultural biotechnologies in Africa. We introduce BioMAISx, the first English language dataset composed of direct quotes pertaining to agricultural biotechnologies extracted from a curated list of Africa-based news sources. We have identified and labelled entities related to key aspects of agricultural biotechnologies, providing valuable insights into public discourse. This dataset can aid in identifying challenges, improving public discourse, and monitoring the perception of agricultural biotechnologies, thus contributing to informed decision-making.

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Additional details

Identifiers

DOI
10.1145/3627673.3679152
Other
oai:uchicago.tind.io:14201

Funding

Schmidt Family Foundation

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Computer Science