Studying the Effects of Text Preprocessing and Ensemble Methods on Sentiment Analysis of Brazilian Portuguese Tweets

Gomes, Fernando Barbosa; Adán-Coello, Juan Manuel; Kintschner, Fernando Ernesto

doi:10.1007/978-3-030-00810-9_15

Cited by 5 publications

(7 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Work studying effects of text preprocessing on SA of Brazilian Portuguese tweets [1] uses heuristics in machine learning algorithms to obtain an accuracy and polarity bias, resulting in increased classification accuracy.…”

Section: A Related Workmentioning

confidence: 99%

“…People across the world give online reviews on products/services. Such data holds value to various stakeholders, creating need for efficient ways to scrape and process this data [1]. In using natural language processing (NLP) techniques, effective preprocessing allows improved detection / interpretation, with significant effects on the results [2].…”

Section: Introductionmentioning

confidence: 99%

“…Hence we propose guidelines for lemmatisation and spell checking use based on priorities for accuracy and time/resource costs. 1 1 Full dataset and code available on GitHub: github.com/Jak-Kav/ICSC_2023_Kavanagh_Greenhow_Jordanous…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the Effects of Lemmatisation and Spell Checking on Sentiment Analysis of Online Reviews

Kavanagh

Greenhow

Jordanous

2023

2023 IEEE 17th International Conference on Semantic Computing (ICSC)

View full text Add to dashboard Cite

With many options for text preprocessing techniques, choosing the most efficient methodology is important for both accuracy and computational expense. Online text often contains non-standard English, spelling errors, colloquialisms, emojis, slang and many other variations that affect current natural language processing tools, with no clear guidelines for preprocessing this type of text. In this work we analyse text preprocessing techniques using a data set of online reviews scraped from iTunes and Google Play store. The objective is to measure the efficacy of different combinations of these techniques to maximise the amount of detected sentiment in a dataset of 438,157 reviews. Sentiment detection was performed by two state-ofthe-art sentiment analysers (RoBERTa and VADER). Statistical analysis of the results suggest preprocessing strategies for maximising sentiment detected within mental health app reviews and similar text formats.

show abstract

Section: A Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessing the Effects of Lemmatisation and Spell Checking on Sentiment Analysis of Online Reviews

Kavanagh

Greenhow

Jordanous

2023

2023 IEEE 17th International Conference on Semantic Computing (ICSC)

View full text Add to dashboard Cite

show abstract

“…Portuguese is the lack of standard annotated datasets. For the accomplishment of the present work we have considered some of the few recent corpus of tweets in Brazilian Portuguese cited in the literature, including the PELESent [3], Tweet-SentBR [4] and BRTweetSentCorpus [5].…”

Section: Datasets For Brazilian Portuguese Sentiment Analysismentioning

confidence: 99%

“…Since we are working with a perfectly balanced dataset, the metric accuracy (percentage of total items classified correctly) seems to be the most adequate to evaluate the models. The experiments used a subset of BRTweetSentCorpus with 3180 positive and 3180 negative tweets, as done by [5], in order to have a baseline to compare our approach. 2 It was used the binary cross-entropy loss function and the adam optimization algorithm to update network weights.…”

Section: Convolutional Neural Net Architecturementioning

confidence: 99%

Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

Coello

Neto

2019

Int J Innov Educ Res

View full text Add to dashboard Cite

Sentiment analysis of texts posted on Twitter is a natural language processing task whose importance has grown along with the increase in the number of users of the platform and the interest of organizations on the opinions of their employees, customers and users.Although Brazil is the sixth country in the world with most active users of Tweeter and Portuguese is the seventh most spoken language in the world, with 221 million speakers (200 million of them living in Brazil), the number of articles that discuss sentiment analysis approaches for Brazilian Portuguese is a small fraction of those that focus on the English language. On the other hand, few works use deep learning for this task when compared with other machine learning and lexical based methods. In this context, the work described in this article addresses the problem using Convolutional Neural Networks (CNN). The paper presents the results of an experimental evaluation that shows that a CNN with a relatively simple architecture can perform much better than a previous approach that uses ensembles of other machine learning classifiers combined with text preprocessing heuristics

show abstract

Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models

Vianna

Carneiro

Carvalho

et al. 2023

Lang Resources & Evaluation

View full text Add to dashboard Cite

Studying the Effects of Text Preprocessing and Ensemble Methods on Sentiment Analysis of Brazilian Portuguese Tweets

Cited by 5 publications

References 9 publications

Assessing the Effects of Lemmatisation and Spell Checking on Sentiment Analysis of Online Reviews

Assessing the Effects of Lemmatisation and Spell Checking on Sentiment Analysis of Online Reviews

Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models

Contact Info

Product

Resources

About