Work

Annotating Targets of Opinions in Arabic using Crowdsourcing

Year: 2015

Type: conference-paper

Abstract: We present a method for annotating targets of opinions in Arabic in a two-stage process using the crowdsourcing tool Amazon Mechanical Turk.The first stage consists of identifying candidate targets "entities" in a given text.The second stage consists of identifying the opinion polarity (positive, negative, or neutral) expressed about a specific entity.We annotate a corpus of Arabic text using this method, selecting our data from online commentaries in different domains.Despite the complexity of the task, we find high agreement.We present detailed analysis.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/w15-3210

Authors: Noura Farra, Kathy McKeown, Nizar Habash

Institutions: Columbia University, New York University Abu Dhabi

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Qatar Foundation, Qatar National Research Fund

OpenAlex ID: W2250979019