Relevant bibliographies by topics / Sentimental novel

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sentimental novel'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Sentimental novel"

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Shabaz, Mohammad, and Ashok Kumar. "AS: a novel sentimental analysis approach." International Journal of Engineering & Technology 7, no. 2.18 (June 5, 2018): 46. http://dx.doi.org/10.14419/ijet.v7i2.27.11679.

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It is interesting to know about the things which are unknown. Just like the emotions, feelings, opinion, sentiments. The term sentimental analysis relates to all these above discussed terms. The extraction of opinion or sentiments from the data through the analysis is called sentimental analysis. There are different kinds of approaches but deal with extraction of sentiments. But none of the approach gives the accurate results. Since sentiments are directly related to human behaviour and human behaviour is not algorithmic. In this paper we have designed another novel approach named as AS analysis. AS analysis is one of new design to overcome the limitation of positive and negative word comparison with input text after tokenization. In this approach we have designed a new formula to find the sentiments count that ranges from -1 to +1 where negative values denotes the negative sentiments and positive values denotes the positive sentiments and 0 denotes the neutral sentiments. By this approach we conclude that the results we have obtained are near to accurate since there is no measure of accuracy it varies from individual to individual, so performing sentimental analysis always gives approximate results.
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Saranya, N., R. Gunavathi, and . "A Novel Sentimental Analysis using Optimized Relevance Vector Machine Classifier." International Journal of Engineering & Technology 7, no. 4.7 (September 27, 2018): 164. http://dx.doi.org/10.14419/ijet.v7i4.7.20536.

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Sentimental analysis is the process of identifying the human’s thoughts or feelings. So Many methods have been developed for the sentimental analysis. Machine learning is one of the widely used approaches towards sentiment classification. In this work, Sentimental analysis is done by using Relevance Vector Machine Classifier with Cuckoo Search Optimization. Here Relevance Vector Machine Classifier (RVMC) is combined with Cuckoo Search Optimization (CSO) for better accuracy and performance. Experiment is made with movie and twitter datasets. Accuracy, precision and recall of all other techniques are evaluated. Here the comparison is made among other algorithms. The result shows that RVMC-CSO algorithm gives accuracy and good performance than other algorithm like SVM, ELM and RVM.
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Margolis, S. "Rescuing the Sentimental Novel." Novel: A Forum on Fiction 42, no. 1 (March 1, 2009): 149–51. http://dx.doi.org/10.1215/00295132-2008-012.

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Stern, Simon. "Sentimental Frauds." Law & Social Inquiry 36, no. 01 (2011): 83–113. http://dx.doi.org/10.1111/j.1747-4469.2010.01224.x.

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The 2006 class action against James Frey, concerning his fabrications in A Million Little Pieces, was the first suit of its kind in the United States. There is nothing new about false memoirs, so what can explain the lawsuit? When the book was promoted on “Oprah's Book Club,” viewers were invited to respond emotionally, and saw their responses as a form of testimony. Those responses produced a sense of betrayal and inauthenticity when Frey's falsehoods were revealed. This view finds support in the eighteenth‐century sentimental novel, which similarly linked readers' reactions to the author's emotional authenticity. Fraud was an ongoing concern for sentimental novelists, some of whom used elaborate editorial to ploys to disavow responsibility for the text, while others populated their novels with fraudulent characters, intended as foils for the protagonist. An investigation of these novels helps to reveal the implications of the Frey case for future claims of literary fraud.
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Roseline, V., and G. Heren Chellam. "A Novel Fusion Attention Algorithm for Sentimental Image Analysis." Indian Journal of Science and Technology 15, no. 9 (March 5, 2022): 386–94. http://dx.doi.org/10.17485/ijst/v15i9.2159.

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Zhu, Yinglin, Wenbin Zheng, and Hong Tang. "Interactive Dual Attention Network for Text Sentiment Classification." Computational Intelligence and Neuroscience 2020 (November 3, 2020): 1–11. http://dx.doi.org/10.1155/2020/8858717.

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Text sentiment classification is an essential research field of natural language processing. Recently, numerous deep learning-based methods for sentiment classification have been proposed and achieved better performances compared with conventional machine learning methods. However, most of the proposed methods ignore the interactive relationship between contextual semantics and sentimental tendency while modeling their text representation. In this paper, we propose a novel Interactive Dual Attention Network (IDAN) model that aims to interactively learn the representation between contextual semantics and sentimental tendency information. Firstly, we design an algorithm that utilizes linguistic resources to obtain sentimental tendency information from text and then extract word embeddings from the BERT (Bidirectional Encoder Representations from Transformers) pretraining model as the embedding layer of IDAN. Next, we use two Bidirectional LSTM (BiLSTM) networks to learn the long-range dependencies of contextual semantics and sentimental tendency information, respectively. Finally, two types of attention mechanisms are implemented in IDAN. One is multihead attention, which is the next layer of BiLSTM and is used to learn the interactive relationship between contextual semantics and sentimental tendency information. The other is global attention that aims to make the model focus on the important parts of the sequence and generate the final representation for classification. These two attention mechanisms enable IDAN to interactively learn the relationship between semantics and sentimental tendency information and improve the classification performance. A large number of experiments on four benchmark datasets show that our IDAN model is superior to competitive methods. Moreover, both the result analysis and the attention weight visualization further demonstrate the effectiveness of our proposed method.
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Nolan, Katherine. "Sarah Scott’s Narrative “No Place”: Gazing and Utopia in Millenium Hall." Eighteenth-Century Fiction 33, no. 4 (June 1, 2021): 513–29. http://dx.doi.org/10.3138/ecf.33.4.513.

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Sarah Scott’s Millenium Hall (1762) is framed by a male narrator for an imagined male reader, and it lacks a substantial critique of slavery, empire, or class; the status of this novel as an example of utopia is therefore an ongoing question. I argue that the utopic vision in the novel happens at the level of fictionality. Millenium Hall is about reforming the sentimental gaze of the male narrator and, by extension, the reader of the novel. Scott critiques sentimentality, particularly the sentimental gaze upon the spectacle of the suffering woman as voyeuristic and inherently sexual. In its stead, she offers a didactic and morally instructive form of looking that avoids titillating scenes of suffering. The novel disrupts and tempers sentimental plots by providing women characters a refuge from sentimentality in the form of the Hall. Renewed attention to Scott’s critique of the sentimental can challenge assumptions about the role of the sentimental mode in eighteenth-century women’s writings.
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Kaur, Chamandeep, Mawahib Sharafeldin Adam Boush, Samar Mansoor Hassen, Wafaa Abushmlah Hakami, Mohammed Hassan Osman Abdalraheem, Najla Mohammed Galam, Nedaa Abdulaziz Hadi, Nedaa Abdulaziz Hadi, and Atheer Omar S. Benjeed. "Incorporating sentimental analysis into development of a hybrid classification model." International journal of health sciences 6, S1 (March 21, 2022): 1709–20. http://dx.doi.org/10.53730/ijhs.v6ns1.4924.

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The Sentimental Analysis approach is typically used for analyzing a user's ideas, sentiments, and text subjectivity, all of which are expressed through text. Sentimental analysis, also known as "opinion mining," is a type of data mining that follows the concept of emotional analysis presented by people in a thoughtful manner. Based on historical evidence, websites are the most effective venue for soliciting customer feedback. Existing methodologies based on sentimental analysis are ineffective. As a result, a novel hybrid framework based on three classifiers, including SVM, logistic regression, and random forest, is proposed in this paper. Based on user feedback or historical data, the hybrid model serves as an effective classifier, assisting in the development of more accurate classification results. Furthermore, the proposed model has worked well and has been compared to other methods based on several performance metrics, such as accuracy, precision, recall, and recall.
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Myungho Lee. "Novel and Sentimental Education: Sympathy and Empathy." Cross-Cultural Studies 53, no. ll (December 2018): 219–49. http://dx.doi.org/10.21049/ccs.2018.53..219.

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Severin, Dorothy Sherman. "The Sentimental Genre: Romance, Novel, or Parody?" La corónica: A Journal of Medieval Hispanic Languages, Literatures, and Cultures 31, no. 2 (2003): 312–15. http://dx.doi.org/10.1353/cor.2003.0057.

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Dissertations / Theses on the topic "Sentimental novel"

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Hart, Hilary. "Sentimental spectacles : the sentimental novel, natural language, and early film performance /." view abstract or download file of text, 2004. http://wwwlib.umi.com/cr/uoregon/fullcit?p3120625.

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Thesis (Ph. D.)--University of Oregon, 2004.
Typescript. Includes vita and abstract. Includes bibliographical references (leaves 176-181). Also available for download via the World Wide Web; free to University of Oregon users.
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Hart, Hilary 1969. "Sentimental spectacles : the sentimental novel, natural language, and early film performance." Thesis, University of Oregon, 2004. http://hdl.handle.net/1794/297.

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Advisor: Mary E. Wood. xii, 181 leaves : ill. ; 29 cm. Print copy also available for check out and consultation in the University of Oregon's library under the call number: PS374.S714 H37 2004.
The nineteenth-century American sentimental novel has only in the last twenty years received consideration from the academy as a legitimate literary tradition. During that time feminist scholars have argued that sentimental novels performed important cultural work and represent an important literary tradition. This dissertation contributes to the scholarship by placing the sentimental novel within a larger context of intellectual history as a tradition that draws upon theoretical sources and is a source itself for later cultural developments. In examining a variety of sentimental novels, I establish the moral sense philosophy as the theoretical basis of the sentimental novel's pathetic appeals and its theories of sociability and justice. The dissertation also addresses the aesthetic features of the sentimental novel and demonstrates again the tradition's connection to moral sense philosophy but within the context of the American elocution revolution. I look at natural language theory to render more legible the moments of emotional spectacle that are the signature of sentimental aesthetics. The second half of the dissertation demonstrates a connection between the sentimental novel and silent film. Both mediums rely on a common aesthetic storehouse for signifying emotions. The last two chapters of the dissertation compare silent film performance with emotional displays in the sentimental novel and in elocution and acting manuals. I also demonstrate that the films of D. W. Griffith, especially The Birth of a Nation, draw upon on the larger conventions of the sentimental novel.
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Taylor, Anne. "Sentimental Journey/Winter Journey: Araki Nobuyoshi's Contemporary Shishōsetsu." Thesis, University of Oregon, 2013. http://hdl.handle.net/1794/13310.

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Senchimentaru na tabi fuyu no tabi or Sentimental Journey/Winter Journey, a photobook created and published by photographer Araki Nobuyoshi in 1991, documented two highly personal events of the photographer's life. The first section consists of twenty-two images of Araki's 1971 honeymoon with his wife Yōko Aoki, while the second section features ninety-one images and an essay documenting the last six months of Yōko's life in 1989-90. This thesis measures SJ/WJ against a Japanese literary tradition invoked by Araki in his opening manifesto: the shishōsetsu. A genre of writing from the early 1900's that read like a confessional or personal diary, the shishōsetsu was regarded as a `true' story insofar as it revealed a totally transparent `author' within a totally transparent `text.' Given these criteria, this thesis determines the success of Araki's SJ/WJ as a true-to-life autobiography.
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Schulz, Melissa N. "Moral fictions girlhood and the material Bible in the sentimental novel /." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/fullcit?p1477932.

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Thesis (M.A.)--University of California, San Diego, 2010.
Title from first page of PDF file (viewed July 13, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (leaves 60-61).
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Woolridge, Robert E. "CONFRONTING MASCULINITY: THE GEN X NOVEL (1984-2000) AND THE SENTIMENTAL MAN." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/dissertations/1670.

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Experimental novels written from 1984-2000 by authors associated with Generation X collectively struggle with common sense notions of masculinity in their various decades at the end of the twentieth century. Relying on confessional, first-person narration, first novels written by white men stage a critical engagement of outdated patriarchal norms in an effort to produce a more progressive masculinity based on sentimentality. In the 1980s, McInerney and Ellis novels, Bright Lights, Big City and Less Than Zero chronicle the struggles of empty, yuppie men who cannot make connections with their peers due to their emotionally devoid lives. By the 1990s, Douglas Coupland proposes a new, sentimental masculinity with his protagonist Andy who narrates Generation X: Tales for an Accelerated Culture. Andy creates sympathetic connections with his peers through the act of confessional storytelling. Chuck Palahniuk’s Fight Club does similar cultural work as Coupland’s novel by creating an anti-sentimental, nameless narrator so bereft of emotion that he creates a hypermasculine alter-ego and violent groups to avoid the emotional emptiness of his life. Finally, Dave Eggers’s A Heartbreaking Work of Staggering Genius (2000) produces the most progressive, evolved masculine narrator, Dave, who spends the entire novel coming to terms with the death of his parents while raising his brother as a son. The novels, in both content and form, become more complex and richer reflecting the development of their protagonists and their philosophical arguments for progressing into sentimental men.
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Ellis, Markman. "The politics of sentimentalism : controversy and polemic in the sentimental novel 1758-1771." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334078.

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Minter, Matt. "Disinterested benevolent sensibility in Henry Mackenzie's The man of feeling, reconsidering the role of Shaftesbury's sentimental philosophy in the rise of the sentimental novel." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0015/MQ48403.pdf.

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Minter, Matt (Matthew John) Carleton University Dissertation English. "Disinterested benevolent sensibility in Henry Mackenzie's The man of feeling; reconsidering the role of Shaftesbury's sentimental philosophy in the rise of the sentimental novel." Ottawa, 1999.

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Bowen, Michael John. "Uncertain affections : representations of trust in the British sentimental novel of the eighteenth century." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38158.

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This thesis examines representations of trust in selected British sentimental novels of the eighteenth century. It focuses principally on the manner in which sentimental prose fiction reflects and participates in the shift from premodern to modern formations of trust. Commenting on the nature of modern trust, Anthony Giddens claims that, with the move to modernity, trust relations in the intimate sphere become increasingly dependent on emotional mutuality, while trust in institutions becomes increasingly impersonal and disengaged from assessments of moral character.
My work explores this dual shift in three sentimental novels. It first analyzes Samuel Richardson's Pamela (1740) and contends that Richardson denies the concept of honor its epistemological role in practical deliberations. The denial of the epistemology of honor uncouples the mechanism of personal trust from assessments of role and role performance and thus makes the trust in persons in the intimate sphere less dependent on institutional forms of trust. To replace honor's role in the formation of trust, Richardson proposes that the sentiments can provide reliable grounds for trust in the intimate sphere. However, he denies the sentiments a role in the formation of an encompassing social trust among strangers and mere acquaintances. The thesis proceeds to read Henry Fielding's Amelia (1751). In order to argue that Fielding envisioned divergent grounds for trust relations, it maintains that Fielding considers trust relations in the intimate sphere and trust relations in public life as based on the sentiments and fair distribution respectively. To conclude, the thesis investigates Oliver Goldsmith's The Vicar of Wakefield (1766) to uncover the manner in which Goldsmith distinguishes personal trust in the intimate sphere from general system trust, which Goldsmith ultimately envisions as an ontological trust in providence.
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Peace, Mary. "The figure of the prostitute in eighteenth-century sentimental discourse : charity, politeness and the novel." Thesis, University of York, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265374.

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Books on the topic "Sentimental novel"

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Barnett, Jill. Sentimental journey: A novel. New York: Pocket Star Books, 2002.

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Cohen, Margaret. The sentimental education of the novel. Princeton, N.J: Princeton University Press, 1999.

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Cavendish, Devonshire Georgiana Spencer. Emma, or, The unfortunate attachment: A sentimental novel. Albany: State University of New York Press, 2004.

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Zwinger, Lynda. Daughters, fathers, and the novel: The sentimental romance of heterosexuality. Madison, Wis: University of Wisconsin Press, 1991.

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Daughters, fathers, and the novel: The sentimental romance of heterosexuality. Madison, Wis: University of Wisconsin Press, 1991.

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Daughters, fathers, and the novel: The sentimental romance of heterosexuality. Madison, Wis: University of Wisconsin Press, 1991.

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Carre, John Le. The naive and sentimental lover. Bath: Chivers P., 1993.

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Carre, John Le. The naive and sentimental lover. Bath: Chivers, 1992.

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Carre, John Le. El amante ingenuo y sentimental. Barcelona: Plaza & Janés Editorial, 1992.

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Carre, John Le. The naive and sentimental lover. South Yarmouth, MA: Curley Pub., 1992.

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Book chapters on the topic "Sentimental novel"

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Hammond, Brean, and Shaun Regan. "The Sympathetic Strain: Sterne and Sentimental Fiction." In Making the Novel, 164–200. London: Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-0-230-80223-0_6.

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Lipski, Jakub. "Sterne's A Sentimental Journey and Contemporary Travel Writing Studies." In Re-Reading the Eighteenth-Century Novel, 75–88. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003153016-5.

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Ward, Candace. "Sensibility, Tropical Disease, and the Eighteenth-Century Sentimental Novel." In Discourses of Slavery and Abolition, 63–77. London: Palgrave Macmillan UK, 2004. http://dx.doi.org/10.1057/9780230522602_5.

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Noble, Marianne. "Making this whole Nation Feel: The Sentimental Novel in the United States." In A Companion to the American Novel, 170–86. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118384329.ch10.

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Richard, Jessica. "The Gambling Man of Feeling: Sublime and Sentimental Gambling." In The Romance of Gambling in the Eighteenth-Century British Novel, 86–110. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230307278_4.

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Skinner, Gillian. "‘Above œconomy’: The History of Lady Barton, The Man of Feeling and A Sentimental Journey." In Sensibility and Economics in the Novel, 91–116. London: Palgrave Macmillan UK, 1999. http://dx.doi.org/10.1057/9780230372566_5.

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Williams, Helen. "Communing with the Fictional Dead: Grave Tourism and the Sentimental Novel." In British Sociability in the European Enlightenment, 41–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-52567-5_4.

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Schultermandl, Silvia. "Catharine Maria Sedgwick’s Clarence, Sentimental Kinship, and the Transnational American Novel of Manners." In Ambivalent Transnational Belonging in American Literature, 50–79. New York : Routledge, 2021. | Series: Routledge transnational perspectives on American literature: Routledge, 2021. http://dx.doi.org/10.4324/9781003129844-3.

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Latif, Muhammad, and Usman Qamar. "A Novel Ensemble Approach for Feature Selection to Improve and Simplify the Sentimental Analysis." In Advances in Intelligent Systems and Computing, 573–92. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22871-2_39.

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Fanasca, Marta. "Tales of lilies and girls’ love. The depiction of female/female relationships in yuri manga." In Studi e saggi, 51–66. Florence: Firenze University Press, 2020. http://dx.doi.org/10.36253/978-88-5518-260-7.03.

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Yuri manga are focused on the representation of sentimental relations between girls. Despite still being a niche within the manga landscape, the popularity of this genre in terms of number of productions and fans is increasing, and in the last few years its fame has been expanding outside Japan as well. As a manga genre, yuri developed since the mid-2000s. Notwithstanding being a novel genre, yuri narratives are deeply embedded into the heritage of the late Meiji-early Shōwa shōjo bunka (girls’ culture), and especially into the so-called “esu kankei” relationships, girl/girl bonds developing in girls’ schools at the time. The aim of this article is double-folded: from one hand, I will highlight and discuss the birth of yuri manga, analysing the re-elaboration of the heritage of shōjo bunka and its cultural productions - such as Yoshiya Nobuko’s Hana Monogatari - into the first examples of yuri manga, to demonstrate the intermediality and intertextuality of these media. On the other hand, I will map the development of yuri manga through the 2000s, stressing onto the increasing relevance given by these narratives to LGBTQ+ related themes, along with the detachment from the influence of shōjo bunka.
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Conference papers on the topic "Sentimental novel"

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Chen, Huimin, Xiaoyuan Yi, Maosong Sun, Wenhao Li, Cheng Yang, and Zhipeng Guo. "Sentiment-Controllable Chinese Poetry Generation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/684.

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Expressing diverse sentiments is one of the main purposes of human poetry creation. Existing Chinese poetry generation models have made great progress in poetry quality, but they all neglected to endow generated poems with specific sentiments. Such defect leads to strong sentiment collapse or bias and thus hurts the diversity and semantics of generated poems. Meanwhile, there are few sentimental Chinese poetry resources for studying. To address this problem, we first collect a manually-labelled sentimental poetry corpus with fine-grained sentiment labels. Then we propose a novel semi-supervised conditional Variational Auto-Encoder model for sentiment-controllable poetry generation. Besides, since poetry is discourse-level text where the polarity and intensity of sentiment could transfer among lines, we incorporate a temporal module to capture sentiment transition patterns among different lines. Experimental results show our model can control the sentiment of not only a whole poem but also each line, and improve the poetry diversity against the state-of-the-art models without losing quality.
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Wang, Ke, and Xiaojun Wan. "SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/618.

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Generating texts of different sentiment labels is getting more and more attention in the area of natural language generation. Recently, Generative Adversarial Net (GAN) has shown promising results in text generation. However, the texts generated by GAN usually suffer from the problems of poor quality, lack of diversity and mode collapse. In this paper, we propose a novel framework - SentiGAN, which has multiple generators and one multi-class discriminator, to address the above problems. In our framework, multiple generators are trained simultaneously, aiming at generating texts of different sentiment labels without supervision. We propose a penalty based objective in the generators to force each of them to generate diversified examples of a specific sentiment label. Moreover, the use of multiple generators and one multi-class discriminator can make each generator focus on generating its own examples of a specific sentiment label accurately. Experimental results on four datasets demonstrate that our model consistently outperforms several state-of-the-art text generation methods in the sentiment accuracy and quality of generated texts.
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Ahmed, Shoiab, and Ajit Danti. "A novel approach for Sentimental Analysis and Opinion Mining based on SentiWordNet using web data." In 2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15). IEEE, 2015. http://dx.doi.org/10.1109/itact.2015.7492646.

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Li, Runnan, Zhiyong Wu, Jia Jia, Yaohua Bu, Sheng Zhao, and Helen Meng. "Towards Discriminative Representation Learning for Speech Emotion Recognition." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/703.

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In intelligent speech interaction, automatic speech emotion recognition (SER) plays an important role in understanding user intention. While sentimental speech has different speaker characteristics but similar acoustic attributes, one vital challenge in SER is how to learn robust and discriminative representations for emotion inferring. In this paper, inspired by human emotion perception, we propose a novel representation learning component (RLC) for SER system, which is constructed with Multi-head Self-attention and Global Context-aware Attention Long Short-Term Memory Recurrent Neutral Network (GCA-LSTM). With the ability of Multi-head Self-attention mechanism in modeling the element-wise correlative dependencies, RLC can exploit the common patterns of sentimental speech features to enhance emotion-salient information importing in representation learning. By employing GCA-LSTM, RLC can selectively focus on emotion-salient factors with the consideration of entire utterance context, and gradually produce discriminative representation for emotion inferring. Experiments on public emotional benchmark database IEMOCAP and a tremendous realistic interaction database demonstrate the outperformance of the proposed SER framework, with 6.6% to 26.7% relative improvement on unweighted accuracy compared to state-of-the-art techniques.
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R. Hodeghatta, Umesh, and Sanath V. Haritsa. "Covid-19 Twitter Sentiments Across the United States in August 2020." In International Conference on AI, Machine Learning and Applications (AIMLA 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111305.

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COVID-19 has drastically affected the entire nation. This study involved collecting tweets and analyzing the COVID tweets for August 2020. The aim was to understand whether people have expressed sentiments related to COVID-19 across all the states of the United States and find any correlation between the sentiment tweets and the number of actual cases reported. Around 400000 COVID-19 Twitter data was collected for August 2020 from the primary Twitter database. A simple NLP-based unigram sentiment analyser, a novel approach different from the traditional machine learning approach, was adopted to identify twitter sentiments. The results indicate that tweets related to COVID demonstrate the two types of sentiments, one related to the deaths and the other about the COVID symptoms. Furthermore, the results show that the sentiments for each category vary from State to State. For example, states of New York, California, Texas are higher tweets sentiments regarding expressing death sentiment, and states of New York, California, Nevada, are higher regarding sentiments of expressing COVID-19 symptoms with an accuracy of 83%. As a part of the research, a new sentiment scorecard was created to provide a sentiment score based on the sentiments of the tweets expressed to the actual reported death cases. The sentiment scores for the ‘symptoms’ class are higher for Maryland, New Jersey, and Oregon, whereas sentiment scores for the 'death' class are higher for Virginia, Delaware, and Hawaii. These sentiment scores indicate that the Twitter users of these states are actively tweeting about symptoms and deaths even though the actual reported cases are less in these states. The analysis results also found no or little correlation between the COVID Tweets and the number of COVID death cases reported across all the states.
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Samraj, Jasmine, and N. Menaka. "Sentimental Analysis Based on Cold-Start Recommendation with Deep Neural Learning (SACNN): A Novel Approach for Travel Recommendation in Pandemic." In 2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC). IEEE, 2021. http://dx.doi.org/10.1109/icmnwc52512.2021.9688450.

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Radaideh, Abdulrahman, Fikri Dweiri, and Mohammad Obaidat. "A Novel Approach to Predict the Real Time Sentimental Analysis by Naive Bayes & RNN Algorithm during the COVID Pandemic in UAE." In 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI). IEEE, 2020. http://dx.doi.org/10.1109/ccci49893.2020.9256587.

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Xing, Bowen, Lejian Liao, Dandan Song, Jingang Wang, Fuzheng Zhang, Zhongyuan Wang, and Heyan Huang. "Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/738.

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Aspect-based sentiment analysis (ABSA) aims to predict fine-grained sentiments of comments with respect to given aspect terms or categories. In previous ABSA methods, the importance of aspect has been realized and verified. Most existing LSTM-based models take aspect into account via the attention mechanism, where the attention weights are calculated after the context is modeled in the form of contextual vectors. However, aspect-related information may be already discarded and aspect-irrelevant information may be retained in classic LSTM cells in the context modeling process, which can be improved to generate more effective context representations. This paper proposes a novel variant of LSTM, termed as aspect-aware LSTM (AA-LSTM), which incorporates aspect information into LSTM cells in the context modeling stage before the attention mechanism. Therefore, our AA-LSTM can dynamically produce aspect-aware contextual representations. We experiment with several representative LSTM-based models by replacing the classic LSTM cells with the AA-LSTM cells. Experimental results on SemEval-2014 Datasets demonstrate the effectiveness of AA-LSTM.
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Chen, Zhenpeng, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, and Xuanzhe Liu. "Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification (Extended Abstract)." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/649.

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Sentiment classification typically relies on a large amount of labeled data. In practice, the availability of labels is highly imbalanced among different languages. To tackle this problem, cross-lingual sentiment classification approaches aim to transfer knowledge learned from one language that has abundant labeled examples (i.e., the source language, usually English) to another language with fewer labels (i.e., the target language). The source and the target languages are usually bridged through off-the-shelf machine translation tools. Through such a channel, cross-language sentiment patterns can be successfully learned from English and transferred into the target languages. This approach, however, often fails to capture sentiment knowledge specific to the target language. In this paper, we employ emojis, which are widely available in many languages, as a new channel to learn both the cross-language and the language-specific sentiment patterns. We propose a novel representation learning method that uses emoji prediction as an instrument to learn respective sentiment-aware representations for each language. The learned representations are then integrated to facilitate cross-lingual sentiment classification.
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Mao, Qianren, Jianxin Li, Senzhang Wang, Yuanning Zhang, Hao Peng, Min He, and Lihong Wang. "Aspect-Based Sentiment Classification with Attentive Neural Turing Machines." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/714.

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Aspect-based sentiment classification aims to identify sentiment polarity expressed towards a given opinion target in a sentence. The sentiment polarity of the target is not only highly determined by sentiment semantic context but also correlated with the concerned opinion target. Existing works cannot effectively capture and store the inter-dependence between the opinion target and its context. To solve this issue, we propose a novel model of Attentive Neural Turing Machines (ANTM). Via interactive read-write operations between an external memory storage and a recurrent controller, ANTM can learn the dependable correlation of the opinion target to context and concentrate on crucial sentiment information. Specifically, ANTM separates the information of storage and computation, which extends the capabilities of the controller to learn and store sequential features. The read and write operations enable ANTM to adaptively keep track of the interactive attention history between memory content and controller state. Moreover, we append target entity embeddings into both input and output of the controller in order to augment the integration of target information. We evaluate our model on SemEval2014 dataset which contains reviews of Laptop and Restaurant domains and Twitter review dataset. Experimental results verify that our model achieves state-of-the-art performance on aspect-based sentiment classification.
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Reports on the topic "Sentimental novel"

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Hassan, Tarek A., Jesse Schreger, Markus Schwedeler, and Ahmed Tahoun. Country Risk. Institute for New Economic Thinking Working Paper Series, March 2021. http://dx.doi.org/10.36687/inetwp157.

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We construct new measures of country risk and sentiment as perceived by global investors and executives using textual analysis of the quarterly earnings calls of publicly listed firms around the world. Our quarterly measures cover 45 countries from 2002-2020. We use our measures to provide a novel characterization of country risk and to provide a harmonized definition of crises. We demonstrate that elevated perceptions of a country's riskiness are associated with significant falls in local asset prices and capital outflows, even after global financial conditions are controlled for. Increases in country risk are associated with reductions in firm-level investment and employment. We also show direct evidence of a novel type of contagion, where foreign risk is transmitted across borders through firm-level exposures. Exposed firms suffer falling market valuations and significantly retrench their hiring and investment in response to crises abroad. Finally, we provide direct evidence that heterogeneous currency loadings on global risk help explain the cross-country pattern of interest rates and currency risk premia.
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