• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of Popular Narrative
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• v.25 no.1
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• pp.429-462
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• 2019

This paper argues how the concept of melodrama can be articulated with the Affect Theory and Posthumanism in relation to animal or environment representation which have emerged as the new topics of the recent era. The argument will be made through the discussion of Agustin Zarzosa's book, Refiguring Melodrama in Film and Television: Captitve Affects, Elastic Sufferings, Vicarious Objects. Using a genealogical approach, the book revisits the notion of mode, affect, suffering (hysteria), and excess which have been dealt with in the existing studies of melodrama. In chapter one, he broadens the concept of melodrama as a mode into the means of redistribution of suffering across the whole society in the mechanism of the duo of evil and virtue. It is the opposition of Brooks's argument in which melodrama functions as the means of proving the distinction between evil and virtue. Chapter two focuses on the fact that melodrama is an elastic system of specification rather than a system of signification, with the perspective of Deleuzian metaphysics. Through the analysis of Home from the Hill (Vincente Minnelli, 1959), this chapter pays attention to an 'affect' generated by the encounters between the bodies and the Mise-en-Scène as a flow not of a meaning but of an affect. Chapter three argues that melodrama should reveal an unloved (woman's) suffering, opposing the discussion on the role of melodrama as the recovery of moral order. Safe (Todd Haynes, 1995), dealing with female suffering caused by the industrial and social environment, elaborates on the arguments on melodrama in relation to female hysteria with ecocritical standpoints. The rest of the two chapters discusses the role of melodrama for the limitation and extension of the notion of the human through 'animal' and 'posthuman' melodrama. It argues that the concept of melodrama as 'excess' and 'sacrifice' blurs the boundary between human and inhuman. In summary, although the author Zarzosa partly agrees with Peter Brook's notion of mode, affect and sufferings,he elaborates the concept of melodrama, by articulating philosophical arguments such as Deleuzianism, feminism, and posthumanism (Akira Lippit and Carry Wolf) with the melodrama. Thefore, Zarzosa challenges the concepts of melodrama led by Brooks, which had been canonical in the field.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.191-221
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• 2019

This study aims to analyze the post-humanistic imagination that has emerged as a major academic thesis in Korean literature, especially novels. In particular, this paper focuses on Cho Ha-hyung's two novels Chimera's Morning(2004) and A Prefabricated Bodhi Tree(2008), published in the early 2000s, for intensive analysis. Post-humanism can be seen as an extension of post-modernism that tried to overcome the limitations of modernity and seek to establish a new world view. In particular, this thought pays attention to the comprehensive understanding of how the rapid development of science and technology, which has developed since the 20th century, has changed the view of humanity and human-centered civilization itself. At the concrete level, it is developing in the direction of constructing a new subject idea by reflecting and dismantling Western-, reason-, and male-centered power mechanisms that are the core of modern civilization. Cho attempts to discover and re-illuminate the surrounding figures, non-humans, and objects that were not noticed in the classic works written in the past. This ideological flow reflects the fact that the concept of human beings, which had been dominated by the humanities in recent years, has been completely changed, and the natural science and technology perspective is applied to the discourse field in various ways. From the point of view of post-humanism, objects that have not been classified as humans and objects that were considered inferior to humans should be included in human or comparable levels. These questions generate interdisciplinary research tasks by involving the large categories of philosophy, such as ontology, epistemology and empirical fields, as well as calling for the participation of the entire literature, science and social sciences. Against the backdrop of a disaster-hit world, Chimera's Morning and A Prefabricated Bodhi Tree depict human beings as variants transformed by bio-technology, and creatures made out of the artificial intelligence built by computer simulations. Post-humanistic ideas in Cho's novels provide a reflective opportunity to comprehensively reconsider the world's shape and human identity reproduced in the text, and to re-explore boundary lines and hierarchy order that distinguish between human and non-human.