Exploring Latent Semantic Information for Textual Emotion Recognition in Blog Articles

Understanding people's emotions through natural language is a challenging task for intelligent systems based on Internet of Things (IoT). The major difficulty is caused by the lack of basic knowledge in emotion expressions with respect to a variety of real world contexts. In this paper, we propose a Bayesian inference method to explore the latent semantic dimensions as contextual information in natural language and to learn the knowledge of emotion expressions based on these semantic dimensions. Our method synchronously infers the latent semantic dimensions as topics in words and predicts the emotion labels in both word-level and document-level texts. The Bayesian inference results enable us to visualize the connection between words and emotions with respect to different semantic dimensions. And by further incorporating a corpus-level hierarchy in the document emotion distribution assumption, we could balance the document emotion recognition results and achieve even better word and document emotion predictions. Our experiment of the word-level and the document-level emotion predictions, based on a well-developed Chinese emotion corpus Ren-CECps, renders both higher accuracy and better robustness in the word-level and the document-level emotion predictions compared to the state-of-the-art emotion prediction algorithms

Examining Accumulated Emotional Traits in Suicide Blogs With an Emotion Topic Model

Suicide has been a major cause of death throughout the world. Recent studies have proved a reliable connection between the emotional traits and suicide. However, detection and prevention of suicide are mostly carried out in the clinical centers, which limits the effective treatments to a restricted group of people. To assist detecting suicide risks among the public, we propose a novel method by exploring the accumulated emotional information from people’s daily writings (i.e. Blogs), and examining these emotional traits which are predictive of suicidal behaviors. A complex emotion topic (CET) model is employed to detect the underlying emotions and emotion-related topics in the Blog streams, based on eight basic emotion categories and five levels of emotion intensities. Since suicide is caused through an accumulative process, we propose three accumulative emotional traits, i.e., accumulation, covariance, and transition of the consecutive Blog emotions, and employ a generalized linear regression algorithm to examine the relationship between emotional traits and suicide risk. Our experiment results suggest that the emotion transition trait turns to be more discriminative of the suicide risk, and that the combination of three traits in linear regression would generate even more discriminative predictions. A classification of the suicide and non-suicide Blog articles in our additional experiment verifies this result. Finally, we conduct a case study of the most commonly mentioned emotion-related topics in the suicidal Blogs, to further understand the association between emotions and thoughts for these authors

The Strength of Olistic Design for Organisation, between effectiveness and disruption

Design refers today to many different aspects, such as product, interior, communication, brand, service and so on. It is possible to provide a coherent perception of a whole environment, designing all the aspects so that they can communicate coherent values and univocal interpretation. This is possible by making the design driven by principles starting from metaphoric models of the mission of a company, translating them into perceptual aspect involving both static elements (layouts, interior design, logo, etc.) and dynamic (interaction protocols, services processes, processes, and so on). Beside the evident advantages of such an approach, problems can arise from conflictual points of view between the company (intended as a unique organism with specific mission and values) and the employees (requiring personal satisfaction, not necessarily coherent with the mission of the organization). The paper describes real experiences exemplifying what indicated, and presents: i) a quick description of the design approach able to design coherent solutions for different artifacts/ services (values identification, required emotions specification, metaphors supporting them, perceptual aspects supporting the metaphors, design of any aspect); ii) the description of a similar approach followed in designing some department in a relevant hospital; iii) the positive effect of the approach evaluated by the positive reactions of patients and nurse; iv) the opposition of the doctors, feeling themselves as interpreted less relevant for the therapies effectiveness; v) the corrective actions taken in order to avoid a disruptive effect of the cohesion between doctors (as more relevant actors of the services) and the rest of the environment. The paper describes the experience, and points out the differences between the design of artifacts for external customers (e.g., cars, white goods, etc,) and the design of environments in which customers and “producers” share the same space and processes, and suggests, for these cases, approaches going beyond User Centered Design.3reservedmixedGALLI, FRANCESCO; MAIOCCHI, MARCO MARIA; PILLAN, MARGHERITAGalli, Francesco; Maiocchi, MARCO MARIA; Pillan, Margherit

Active Learning With Complementary Sampling for Instructing Class-Biased Multi-Label Text Emotion Classification

High-quality corpora have been very scarce for the text emotion research. Existing corpora with multi-label emotion annotations have been either too small or too class-biased to properly support a supervised emotion learning. In this paper, we propose a novel active learning method for efficiently instructing the human annotations for a less-biased and high-quality multi-label emotion corpus. Specifically, to compensate annotation for the minority-class examples, we propose a complementary sampling strategy based on unlabeled resources by measuring a probabilistic distance between the expected emotion label distribution in a temporary corpus and an uniform distribution. Qualitative evaluations are also given to the unlabeled examples, in which we evaluate the model uncertainties for multi-label emotion predictions, their syntactic representativeness for the other unlabeled examples, and their diverseness to the labeled examples, for a high-quality sampling. Through active learning, a supervised emotion classifier gets progressively improved by learning from these new examples. Experiment results suggest that by following these sampling strategies we can develop a corpus of high-quality examples with significantly relieved bias for emotion classes. Compared to the learning procedures based on traditional active learning algorithms, our learning procedure indicates the most efficient learning curve and estimates the best multi-label emotion predictions

Narrative Approaches to Wellbeing

The importance of narratives in therapeutic processes such as convalescence, psychotherapy and counselling is well-established. Such narrative-based approaches highlight the benefit of sense-making, coping and positive affect in circumstances of illness or psychological distress. These phenomena are consistent with theories of narrative which emphasise contextualisation and the restoration of equilibrium. This paper proposes to open up further areas of enquiry by examining a range of theoretical models of narrative as an imaginative space. It will examine a selection of established models of narrative in literary and media disciplines, and identify some themes and categories which recur in the practice of story-telling – such as inevitability and agency, community and individuality, freedom and destiny, absurdity and purpose. The paper will conclude by articulating some of the major themes that narrative suggests as a discipline, and which therefore might prove fruitful in understanding not only how story-telling plays a part in therapeutic processes, but how narrative might help to formulate a more generalised notion of wellbeing

\u3ci\u3eThe Nebraska Educator,\u3c/i\u3e Volume 3: 2016 (complete issue)

There are not many student-run academic journals, so The Nebraska Educator is excited to provide a forum for researchers, scholars, policymakers, practitioners, teachers, students, and informed observers in education and related fields in educational settings in the United States and abroad. Now in our third year, it is exciting to see the work that continues to be accomplished when those interested in educational research have a venue to share their contributions. To date, articles published in the previous two volumes of our journal have been downloaded more than 7,000 times by readers all across the globe. The Nebraska Educator has four main goals with its published research: (1) to familiarize students with the publication process, (2) to faciliate dialogue between emerging scholars, educators, and the larger community, (3) to promote collegiality and interdisciplinary awareness, and (4) to establish a mechanism for networking and collaboration. This publication would not have been possible without the guidance and assistance from faculty, staff, and graduate students across the College of Education and Human Sciences. We are also grateful for the work of Paul Royster at Love Library, who assisted us with the final formatting and online publication of our journal. In addition, we would like to thank the Department of Teaching, Learning, and Teacher Education’s Graduate Student Assocation, whose financial contributions helped to launch our journal. The Nebraska Educator is an open-access peer-reviewed academic education journal at the University of Nebraska-Lincoln. This journal is produced by UNL graduate students and publishes articles on a broad range of education topics that are timely and have relevance at all levels of education. We seek original research that covers topics which include by are not limited to: (a) curriculum, teaching, and professional development; (b) education policy, practice, and analysis; (c) literacy, language, and culture; (d) school, society, and reform; and (e) teaching and learning with technologies. If you are interested in submitting your work to The Nebraska Educator, please submit online using: http://digitalcommons.unl.edu/nebeducator/ Contents of Volume 3 Examining doctoral attrition: A self-determination theory approach, by Mark Beck Korea and the Dominican Republic: A transnational case study-analysis, by Aprille Phillips Transitional Adjustment Intervention for International Students in U.S. Colleges, by Zhuo Chen Language, Literacy, and Dewey: “Experience” in the Language Arts Context, by Jessica Masterson Fostering Metacognition in K-12 Classrooms: Recommendations for Practice, by Markeya S. Peteranetz A Technology-Supported Learning Experience to Facilitate Chinese Character Acquisition, by Xianquan Liu and Justin Olmanso

Negative Emotions in Fieldwork: A Narrative Inquiry of Three EFL Researchers’ Lived Experiences

Through narrative inquiry this research depicts and interprets the negative emotions that three English as Foreign Language (EFL) researchers experienced in different research sites during their fieldwork. Narrative inquiry informs the design of this investigation as the approach is particularly useful for understanding lived experiences. The study draws on autobiographical as well as narrative data to report the negative emotions that evolve during English language education fieldwork, an aspect absent in the existing literature. Findings suggest that the researchers experienced a wide range of negative emotions namely ethical dilemma, anger, anxiety, guilt, and shame. These results carry implications for language education research methodology, teaching, and fieldwork related ethical requirements of Institutional Review Board (IRB), and language education researchers’ necessary psychological support