Contextual Sentiment Analysis with Untrained Annotators

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style="font-size:.9rem">Contextual Sentiment Analysis with Untrained Annotators</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lucas%20A.%20Silva">Lucas A. Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=Carla%20R.%20Aguiar"> Carla R. Aguiar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents a proposal to perform contextual sentiment analysis using a supervised learning algorithm and disregarding the extensive training of annotators. To achieve this goal, a web platform was developed to perform the entire procedure outlined in this paper. The main contribution of the pipeline described in this article is to simplify and automate the annotation process through a system of analysis of congruence between the notes. This ensured satisfactory results even without using specialized annotators in the context of the research, avoiding the generation of biased training data for the classifiers. For this, a case study was conducted in a blog of entrepreneurship. The experimental results were consistent with the literature related annotation using formalized process with experts. <iframe src="https://publications.waset.org/abstracts/2725.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sentiment%20analysis" title="sentiment analysis">sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=untrained%20annotators" title=" untrained annotators"> untrained annotators</a>, <a href="https://publications.waset.org/abstracts/search?q=naive%20bayes" title=" naive bayes"> naive bayes</a>, <a href="https://publications.waset.org/abstracts/search?q=entrepreneurship" title=" entrepreneurship"> entrepreneurship</a>, <a href="https://publications.waset.org/abstracts/search?q=contextualized%20classifier" title=" contextualized classifier"> contextualized classifier</a> </p> <a 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Contextual Sentiment Analysis with Untrained Annotators