Sentiment analysis has increasingly gained significance in commercial settings, driven by the rising impact of reviews on purchase decision-making in recent years. This research conducts a thorough examination of the suitability of machine learning and deep learning approaches for sentiment analysis, using Romanian reviews as a case study, with the aim of gaining insights…
Identifying the sentiment of collected tweets has become a challenging and interesting task. In addition, mining and defining relevant features that can improve the quality of a classification system is crucial. The data modeling phase is fundamental for the whole process since it can reveal hidden information from the textual inputs. Two models are…
Twitter Sentiment Analysis shows several challenges due to the platform’s features (e.g., short messages, colloquial style, etc.). People want to express their ideas related to personality, events, or breaking news. Social media is one of the fastest ways to express opinions, and research directions are developed to analyze the polarity of written messages. Very…
The USA presidential election in 2020 has aroused the interest of society as a whole. Social media plays an essential role in campaigns due to how people express their ideas about a candidate. Therefore, analyzing messages posted on environments like Twitter is a challenging task that can be accomplished using sentiment analysis techniques. Our…
Twitter Sentiment Analysis is demanding due to the freestyle way people express their opinions and feelings. Using only the preprocessed text from a dataset does not bring enough value to the process. Therefore, there is a need to define and mine different and complex features to detect hidden information from a tweet. The proposed…
In the last years, a wide range of new similarity measures has been designed and applied to different contexts. Currently, there’s a deep lack in the validation and evaluation steps for novel similarities. In general, new measures are validated mostly through numerical experiments using different data sets. But this is not enough, as in…