• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.647-649
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• 2023

Sentiment analysis as part of natural language processing (NLP) has received much attention following the demand to understand people's opinions. Aspect-based sentiment analysis (ABSA) is a fine-grained subtask from sentiment analysis that aims to classify sentiment at the aspect level. Throughout the years, researchers have formulated ABSA into various tasks for different scenarios. Unlike the early works, the current ABSA utilizes many elements to improve performance and provide more details to produce informative results. These ABSA formulations have provided greater challenges for researchers. However, it is difficult to explore ABSA's works due to the many different formulations, terms, and results. In this paper, we conduct a comparative analysis of recent studies on ABSA. We mention some key elements, problem formulations, and datasets currently utilized by most ABSA communities. Also, we conduct a short review of the latest papers to find the current state-of-the-art model. From our observations, we found that span-level representation is an important feature in solving the ABSA problem, while multi-task learning and generative approach look promising. Finally, we review some open challenges and further directions for ABSA research in the future.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.160-161
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• 2017

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language Opinion mining and sentiment analysis(OMSA) as a research discipline has emerged during last 15 years and provides a methodology to computationally process the unstructured data mainly to extract opinions and identify their sentiments. The relatively new but fast growing research discipline has changed a lot during these years. This paper presents a scientometric analysis of research work done on OMSA during 2007-2016. For the literature analysis, research publications indexed in Web of Science (WoS) database are used as input data. The publication data is analyzed computationally to identify year-wise publication pattern, rate of growth of publications, research areas. More detailed manual analysis of the data is also performed to identify popular approaches (machine learning and lexcon-based) used in these publications, levels (documents, sentences or aspect-level) of sentiment analysis work done and major application areass of OMSA.

• Journal of Information Science Theory and Practice
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• v.1 no.2
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• pp.36-57
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• 2013

Blogs are readily available sources of opinions and sentiments which allows bloggers to exert a certain level of influence over the blog readers. Previous studies had attempted to analyze blog features to detect influence within the blogosphere, but had not studied in details influence at the blogger-level. Other studies studied bloggers' personalities with regards to their propensity to blog, but did not relate the personalities of bloggers to influence. Bloggers may differ in their way or manner of exerting influence. For example, bloggers could be active participants or just passive shares, or whether they express ideas in a rational or subjective manner, or they are received positively or negatively by the readers. In this paper, we further analyze the engagement style (frequency, scope, originality, and consistency of the blog postings), persuasion style (appeals to reasons or emotions), and persona (degree of compliance) of individual bloggers. Methods used include similarity analysis to detect the sharing-creating aspect of engagement style, subjectivity analysis to measure persuasion style, and sentiment analysis to identify persona style. While previous studies analyzed influence at blog site level, our model is shown to provide a fine-grained influence analysis that could further differentiate the bloggers' influence style in a blog site.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.57-66
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• 2022

The aim of the article is to investigate socio-political processes in Ukraine on the basis of institutional and behavioral approaches, in particular their regulatory and informational support. Methodology. To determine the nature and content of sociopolitical processes, the following approaches have been used: 1. Institutional approach in order to analyze the development of Ukraine's political institutions. 2. The behavioral approach has been used for the analysis of socio-political processes in Ukraine in the context of political behavior of citizens, their political activity which forms the political culture of the country. Results. The general features of the socio-political situation in Ukraine are as follows: the formed model of government, which can be conditionally described as "presidential"; public demand for new leaders remains at a high level; the society has no common vision of further development; significant tendency of reduction of real incomes of a significant part of the society and strengthening of fiscal pressure on businessmen will get a public response after some time. Increasing levels of voice, accountability, efficiency of governance and the quality of the regulatory environment indicate a slow change in the political system, which will have a positive impact on public sentiment in the future. At the same time, there has been little change in the quality of Ukraine's institutions to ensure political stability, the rule of law and control of corruption. There are no cardinal changes in the development of the institution of property rights, protection of intellectual rights, changes in the sphere of ethics and control of corruption. Thus, Ukraine's political institutions have not been able to bring about any change in the social-political processes. Accordingly, an average level of trust and confidence of citizens in political institutions and negative public sentiment regarding their perception and future change can be traced in Ukraine.