• Ei tuloksia

Abroad, A. M., & Kolb, D. (2011). Using Experiential Learning Theory to Promote Student Learning and Development in Programs of Education: Case Western Reserve University . (M. P.

Michael Vande Berg, Ed.) Stylus Publishing.

Alhawiti, K. (2014). Natural Language Processing and its Use in Education. International Journal of Advanced Computer Science and Applications, 5(12), pp. 72-76.

Alm, C., Roth, D., & Sproat, R. (2005). Emotions from text: machine learning for text-based emotion prediction. In procedings of the conference on Human Language Technology and empirical methods in Natural Language Processing (pp. 579-586). Association of Computational Linguistics.

Aman, S., & Szpakowicz, S. (2007). Identifying expressions of emotion in text. In procedings of International Conference on Text, Speech and Dialogue , pp. 196-205.

Arbona, C. (2000). The development of academic achievement in school aged children: Precursors to career development. (Brown, Ed.) New York: John Wiley & Sons.: Handbook of counseling psychology .

Archer, L. (1984). Systematic method for designers. (N. Cross, Ed.) London: John Wiley:

Developments in design methodology.

Aronson, E., Wilson, T., & Akert, R. (2005). Social psychology ( 7th ed. ed.). Upper Saddle River, New York: Pearson Education, Inc.

Arthur, S. L. (1959). Some Studies in Machine Learning Using the Game of Checkers. BM Journal of Research and Development.

Artstein, R., & Poesio, M. (2008). Inter-coder agreement for computational linguistics.

Computer Linguistics. 34(4), pp 555-596.

Atria, M., Strohmeier, D., & Spiel, C. (2007). The relevance of the school class as social unit for the prevalence of bullying and victimization.European Journal of Developmental Psychology, 4(4), pp. 372-387.

Au, Y. (2001). Design Science: The Role of Design Science in Electronic Commerce Research.

Communications of the Association for Information Systems, 7.

Awinsong, M., Dawson, O., & Gidiglo, B. E. (2015). Students' Perception of the role of Counsellors in the Choice of a Careeer: Astudy of the Mfatsipim Municipality in Ghana. International journal of Learning and education research, 13(3), pp.79-99.

Aylward, N., Harrison, K., Jackson, C., Merton, B., & Newman , E. (2003). Explaining Personal and Social Development. Queen's Printer.

Bambling, M., R., K., Reid, W., & Wegner, K. (2008). Online counselling: The experience of counsellors providing synchronous single-session counselling to young people.

Counselling and Psychotherapy Research, 8(2).

Barrett, L. (2006). Emotions as natural kinds?. Perspectives on Psychological Science. 1, pp. 28-58.

Baumeister , R. F., & Bushman , B. (2007). Angry emotions and aggressive behaviors. (H. &. Huber,

& Ashland, Eds.) OH.

Baumeister, R. F., DeWall, C. N., Vohs, K. D., & Alquist, J. L. (2010). Does emotion cause behavior (apart from making people do stupid, destructive things). Then a miracle occurs: Focusing on behavior in social psychological theory and research, pp. 12-27.

110

Bellegarda, J. (2010). Emotion analysis using latent affective folding and embedding. In Proceedings of the NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text,. Los Angeles, California .

Bhowmick, P., Mitra, P., & Anupam, B. (2008). An agreement measure for determining inter-annotator reliability of human judgement affective text. In proceedings of the workshop on human judgements in computational linquistics, (pp. 58 - 65). Manchester, UK.

Boiy, E., Hens, P., Deschacht, K., & Moens, M. F. (2007). Automatic Sentiment Analysis in On-line Text. ELPUB, (pp. 349-360).

Buitinck, L., Amerongen, J., E., T., & De Rijke, M. (2015). Multi-emotion detection in user-generated reviews. In European Conference on Information Retrieval. Springer International Publishing.

Burget, J., Karasek, J., & Smekal, Z. (2011). Recognition of Emotions in Czech Newspaper Headlines. Radioengineering, 20(1), pp. 39 - 47.

Burstein, J., Shore, J., Sabatini, J., Moulder, B., Holtzman, S., & Pedersen, T. (2012). The language musesm system: Linguistically focused instructional authoring. 2.

Cambria, E., & White, B. (2014). Jumping NLP curves: A review of natural language processing research. IEEE Computational Intelligence Magazine, 9(2), 48-57.

Canales, L., & Martinez-Barco, P. (2014). Emotion Detection from text: A Survey. . In proceddings of 11th International Workshop on Natural Language Processing and Cognitive Science - NAACL.

Cannon, W. (1972). The James-Lange Theory of Emotions: A Critical Examination and an Alternative Theory. The American Journal of Psychology., 39, pp. 106–124. .

Carey, J., & Harrington, K. M. (2010). Nebraska school counseling evaluation report. Center for School Counseling Outcome Research and Evaluation.

Chapman, W., Fizman, M., Chapman, B., & Haug, P. J. (2001). A Comparison of Classification Algorithms to Automatically Identify Chest X-Ray Reports That Support Pneumonia.

journal of biomedical informatics, 34, pp. 4 - 14.

Chopade, C. (2015). Text based emotion recognition: A survey. International journal of science and research , 4(6), pp. 409- 414.

Cohen, J. (1960). Coefficient of agreement for nominal scale. Education and Psychological Measurement, 20(1), pp. 37–46.

Conger, A. (1980). Integration and generalization of kappas for multiple raters. Psychological Bulletin., 88, pp. 322–328.

Cotton, J. L. (1981). A review of research on Schachter's theory of emotion and the misattribution of Arousal. European Journal of Social Psychology., 11, pp. 365–397.

Coupel, T. (2014). What is the difference between Natural Language Generation and Understanding? Retrieved from What is the difference between Natural Language Generation and Understanding?: https://yseop.com/blog/what-is-the-difference-between-natural-language-generation-and-understanding-2/

Cronbach, L. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), pp. 297–334.

Crowston, K., Liu, X., & Allen, E. E. (2010). Machine learning and rule-based automated coding of qualitative data. In proceedings of the American Society for Information Science and Technology, 47, pp. 1-2.

Daly, E. J., Duhon, G. J., & Witt, J. C. (2002). Proactive approaches for identifying and treating children at risk for academic failure. (F. M. In K. L. Lane, Ed.) Boston: Allyn & Bacon.:

Interventions for children with or at risk for emotional and behavioral disorders.

111 Damasio, A. (2000). The Science of Emotions. Retrieved from: The Science of Emotion

Executive Summary: http://www.loc.gov/loc/brain/emotion/Damasio.html De Heer-Menlah, F. K. (2002). Internet acess for African countries. Ubiquity, 4.

De Smedt, K. (2009). NLP for writing: What has changed? NEALT proceedings series, 3.

Devaney, E., O’Brien, M. U., Resnik, H., Keister, S., & Weissberg, R. P. (2006). Sustainable schoolwide social and emotional learning (SEL): Implementation guide and toolkit.

Chicago, IL: CASEL.

Dutton, D. G., & Aron, A. P. (1974). Some evidence for heightened sexual attraction under conditions of high anxiety. Journal of Personality and Social Psychology, 30(4), pp. 510–

517.

Duveskog, M., Kemppainen, K., Bednarik, R., & Sutinen, E. (2009, june). Designing a story-based platform for HIV and AIDS counseling with Tanzanian children. In Proceedings of the 8th International Conference on Interaction Design and Children (pp. 27-35). ACM.

Dzikovska, M., Nielsen, R., Brew, C., Leacock, C., Gi- ampiccolo, D., & and Bentivogli, L.

(2013). An overview of spoken language tech- nology for education. In Proceed- ings 6th International Workshop on Semantic Evaluation.

Eekels, J., & Roozenburg, N. (1991). A methodological comparison of the structures of scientific research and engineering design: their similarities and differences. . Design Studies, 12(4), pp. 197-203.

Ekman, P. (1999). Basic emotions. In Handbook of cognition and emotion. pp. 45–60.

Ekman, P. (2007). Emotions revealed: Recognizing faces and feelings to improve communication and emotional life.

Elias, M. J., Arnold, H., & Hussey, C. (2003). EQ+IQ: Best leadership practices for caring and successful schools. Thousand Oaks, CA: Corwin.

Essuman, J. (2001). A review of educational studies (1983-1997) in guidance and counselling in schools in Ghana. Ghana J. Psychol., 1(1), pp. 72-88.

Fang, X., & Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(1), pp. 1-14.

Fleiss, J. (1971). Measuring nornimal scale agreement among many raters. Psychological Bulletin, 76, pp. 378-382.

Fletcher-Tomenius, L., & Vossler, A. (2009). Trust in online therapeutic relationships: The therapist's experience. Counselling Psychology Review, 24(2), pp. 24-34.

Fox, C., & Butler, I. (2007). If you don't want to tell anyone else you can tell her’: young people's views on school counselling. British Journal of Guidance & Counselling, 35, PP. 97-114.

Frijda, N. H., Kuipers, P., & Schure, E. (1989). Relations among emotion, appraisal, and emotional action readiness’. Journal of Personality and Social Psychology, 57(2), pp. 212–

228.

Fulcher, A., & Hills, P. (1996). Towards a strategic framework for design research. Journal of Engineering Design, 7(1), pp. 183-193.

Geertzen, J. (2012). Inter-Rater Agreement with multiple raters and variables. Retrieved from https://nlp-ml.io/jg/software/ira/

Genereux, M., & Evans, R. P. (2006). Distinguishing affective states in weblogs. In Proceedings of the AAAI Spring Symposium on Computational Approaches to Analysing Weblogs,, (pp.

27–29). Stanford, California.

Ghana National report, b. e. (2004). The development of education. Retrieved may 21, 2017, from http://www.ibe.unesco.org/National_Reports/ICE_2004/ghana.pdf

Gilbert, D. (2006). Stumbling on happiness. New York, NY: Knopf.

112

Gladding, S. (2004). Counseling: A Comprehensive Profession (5th edition). Upper Saddle River, NJ:, Merrill/Prentice Hall.

Glasheen, K., Campbell, M., & Shochet, I. (2013). Opportunities and Challenges: School Guidance Counsellors’ Perceptions of Counselling Students Online. Australian Journal of Guidance and Counselling, 23, pp. 222- 235.

Gold , R. (2000). AIDS education for gay men: towards a more cognitive approach AIDS Care.

12, pp. 267–272.

Griffiths, P. (2002). Jesse Prinz Gut Reactions: A Perceptual Theory of Emotion. The British Journal for the Philosophy of Science, 59(3), pp. 559-559.

Gupta, N., Gilbert, M., & Fabbrizio, G. (2010). Emotion Detection in Email Customer Care. In Workshop on Computational Approaches to Analysis and Generation of Emotion in Text.

NAACLIHLT 2010. Los Angeles.

Gutnik, L. A., Hakimzada, A. F., Yoskowitz, N. A., & Patel, V. L. (2006). The role of emotion in decision-making: A cognitive neuroeconomic approach towards understanding sexual risk behavior. Journal of biomedical informatics, 39(6), pp. 720-736.

Hancock, J., Landrigan, C., & Silver, C. (2007). Expressing emotion in text-based communication. In procedingsof the SIGCHI conference on human factors in computing system systems (pp. 929 - 932). ACM.

Hannan, A. (2015). Emotion Detection from Text. International Journal of Engineering Research and Development, 11(7), pp. 23 - 34 .

Hashem, E., & Mabrouk, M. (2014). A Study of Support Vector Machine Algorithm for Liver Disease Diagnosis. American Journal of Intelligent Systems, 4(1), pp. 9-14.

Hassan , S., Rafi , M., & Shaikh , M. (2011 ). Comparing SVM and naive bayes classifiers for text categorization with Wikitology as knowledge enrichment. In Proceedings of Multitopic Conference (INMIC), . 14, pp. 31-34. IEEE.

Haward, M., & Janvier, A. (2015). An introduction to behavioural decision-making theories for paediatricians. Foundation Acta Pædiatrica, 104(4), Pp. 340–345.

Hevner , A. R., March , S. T., Park , J., & Ram , S. (2004, March). Design science in information systems research. MIS Quarterly, 28(1), 75-105.

Hevner, A. (2007). A three-cycle view of design science research. Scandinavian Journal of Information Systems, 19(22), 87–92.

Hevner, A., March, S., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. . MIS Quarterly , 28, 75-105.

Huang , T., Huang, C., & Chuang, Y. (2016). Change discovery of learning performance in dynamic educational environments. Telematics and Informatics, 33(3), pp. 773-792.

Inman, A., Ngoubene-Atioky, A., Ladany, N., & Mack, T. (2009). School Counselors in International School: Critical Issues and Challenges. International Journal of Advance Counselling , 31, pp. 80 – 99.

Izard, C. E. (1992). Basic emotions, relations among emotions, and emotion-cognition relations.

Psychological Review, 99(3), pp. 561–565.

Jadhav, A., & Gadekar, D. (2004). A Survey on Text Mining and Its Techniques. International Journal of Science and Research (IJSR), 3(11), pp. 2110- 2113.

Jaeger, A., & Eagan, M. K. (2007). Exploring the value of emotional intelligence: A means to improve academic performance. NASPA Journal, 44(3).

Jain, U., & Punjab, R. (2015). International journal of current engineering and Technology . A review on the emotion detection from text using machine learning technique, 5(4), pp. 1-6.

113 Jenkins, P., & Palmer, P. (2012). At risk of harm‟? An exploratory survey of school counsellors in the UK, their perceptions of confidentiality, information sharing and risk management. British Journal of Guidance & Counselling, 40(5), pp. 545-559.

Johannesson, P., & Perjons. (2012). A design Science Primer. Create Space Independent Publishing Platform., pp. 144 .

John, D., Boucouvalas, A. C., & Xu, Z. (2006). Representing emotional momentum within expressive internet communication. In Proceedings of the 24th International Conference on Internet and Multimedia Systems and Applications (pp. 183–188). Anaheim, CA.:

ACTA Press.

Johnson-Laird, P. N., & Oatley, K. (1989). The language of emotions: An analysis of a semantic field. Cognition and Emotion , 3(2), pp. 81–123.

Jones, K. (1994). Natural Language Processing: A historical Review. Current issues in computational linguistics: in honour of Don Walker., pp. 3-16.

Kannan, J., & Miller, J. L. (2009). The positive role of negative emotions: Fear, anxiety, conflict and resistance as productive experiences in academic study and in the emergence of learner autonomy. International Journal of Teaching and Learning in Higher Education, 20(2), pp. 144-154.

Kano, E. (2012). Guidance and counselling services in Tanzanian schools: the Caliber of personnel and constraints. Dar es Salaam:. LAP LAMBERT Academic Publishing.

Kao, E. C.-C., Yang, T.-H., Hsieh, C.-T., & Soo, V.-W. (2009). Towards Text-based emotion detection: A survey and possible improvement. In international conference on information management and engineering (pp. 70-74). IEEE.

Keltner, D., Ekman, P., Gonzaga, G., & J., B. (2010). Facial expression of emotion. In Handbook of affective sciences. (K. S. RJ Davidson, Ed.) New York, NY: Oxford University Press.

Keltner, D., Kogan, A., Piff, P. K., & Saturn, S. R. (2014). The sociocultural appraisals, values, and emotions (SAVE) framework of prosociality: Core processes from gene to meme.

Annual Review of Psychology, 65, pp. 425–460.

Khandelwal, T., Joshi, G., & Singhania, A. (2013). Semantic Web-Based E-Counseling System.

International Journal of Computer Science and Electronics Engineering (IJCSEE), 1(1), pp.

70- 74.

Kim, S. (2011). Recognising Emotions and Sentiments in Text. Ph.D. thesis, University of Sydney.

Kiritchenko, S., Zhu, X., & Mohammad, S. M. (2004). Sentiment analysis of short informal texts.

Journal of Artificial Intelligence Research, 50, pp. 723-762.

Kolog, E. A. (2014). E-counselling implementation: Contextualized approach. Masters Thesis University of Eastern Finland.

Kolog, E. A., & Suero Montero, C. (2017). Towards Automated e-Counselling System Based on Counsellors' Emotion Perception. Education and information technologies(In Press).

Kolog, E. A., Montero, S. C., & Sutinen, E. (2016). Annotation Agreement of Emotions in Text:

The Influence of Counselors' Emotional State on their Emotion Perception. In proceeding of of International Conference on Advanced Learning Technologies (ICALT) (pp.

357-359). Austin,Texas, USA: IEEE.

Kolog, E. A., Sutinen, E., & Vanhalakka-Ruoho, M. (2014). E-counselling implementation:

Students’ Life stories and counselling technologies in perspective. International Journal of Education and Development using Information and Communication Technology, 10(3), pp. 32-48.

Kolog, E. A., Sutinen, E., & Vanhalakka-Ruoho, M. (2015). Towards students’ behavioural intention to adopt and use counselling: An empirical approach of using Unified

114

Theory of Acceptance and Use of Technology Model. In procedings of AFRICON. 13, pp. 1-6. Adis Ababa: IEEE.

Kolog, E. A., Sutinen, E., & Vanhalakka-Ruoho, M. (2015). Using Unified Theory of Acceptance and Use of Technology Model to Predict Students’ Behavioral Intention to Adopt and Use E - Counseling in Ghana. International Journal of Modern Education and Computer Science, 7(11), 1-11.

Krippendoff, K. (1967). Content Analysis: An Introduction to its Methodology. Sage Publications.

Kuhn, L. (2004). Student perception of school counselor roles and functions. Master’s thesis, University of Maryland, College Park.

Landis, J., & Kouch, G. (1977). The measurement of Observer agreement for categorical data.

Biometrics, 33(1), pp. 159–174. .

Langelier, C. (2005). Emotions and Learning: Where brain based reseach and cognitive-behavioural counselling strategies meet the road. River jiurnal online academic Journal, 1(1), pp. 1 - 13.

Lazarus, & S., R. (1991). Progress on a cognitive-motivational-relational theory of Emotion.

American Psychologist, 46(8), pp 819-834.

Lazarus, R. S. (1966). Psychological stress and the coping process. New York: McGraw-Hill.

Le Surf, L., & Leech, A. (1999). Exploring young people‟s perceptions relevant to counselling:

a qualitative study . British Journal of Guidance and Counselling, 27, 152.

Leacock, C., Chodorow, M., Gamon, M., & and Tetreault, J. (2010). Automated grammatical error detection for language learners. Synthesis lectures on human language technologies, 3(1), pp. 1–134.

Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and decision making. Annual Review of Psychology, 66, pp. 799-823.

Lerner, J., Gonzalez, R., Small, D., & Fischhoff, B. (2003). Effects of fear and anger on perceived risks of terrorism: A national field experiment. Psychological Science, 14, pp. 144-50.

Lerner, J., Li, Y., Valdesolo, P., & Kassam, K. S. (2014). Emotion and decision making. Annual Review of Psychology, 66, pp 799-823.

Levenson, R. W., Ekman, P., Heider, K., & Friesen, W. V. (1992). Emotion and autonomic nervous system activity in the Minangkabau of West Sumatra. Journal of Personality and Social Psychology, 62(6), pp. 972–988.

Liew, J. E. (2012). Control, executive functions, and education: Bringing self-regulatory and socialemotional competencies to the table. Child Development Perspectives., 6, pp. 105–

111.

Light, R. (1971). Measures of Response agreement for qualitative data: some generalizations and alternatives. Psychological bulletin, 76(1), pp. 365-377.

Litman, D. (2016). Natural Language Processing for Enhancing Teaching and Learning. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), (pp.

4170-4176).

Littlechild, B. (2012). Values and cultural issues in social work. Eris Web Journal.

Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synth. Lect. Human Language Technology, 5(1), pp. 1-167.

Liu, H., Lieberman, H., & & Selker, T. (2003). A model of textual affect sensing using realworld knowledge. In Proceedings of the 8th International Conference on Intelligent User Interfaces, IUI ’03, (pp. 125–132,). New York, NY. ACM.

115 Loewenstein , G. (1996). Out of control: visceral influences on behavior. Organ Behav Hum Decis

Process, 65, pp. 272–292.

Loewenstein , G., Weber , E., Hsee , C., & Welch , N. (2001). Risk as feelings. Psychological Bulletin , 127, pp. 267-86.

Low, G. R., & Nelson, D. B. (2006). Emotional Intelligence and college uccess: A research-based assessment and intervention. In proceedings of 39th Annual Conference of the College Reading and Learning Association and the 25th Annual Conference of College Academic Support Programs, Austin, Texas. .

Lowenstein, G., & Lerner, J. S. (2003). The role of affect in decision making. (K. S. In R. Davidson, Ed.) New York: Oxford University Press.

Lu, C. Y., H., S., Liu, J. C., Cruz - Lara, S., & Hong, J. S. (2010). Automatic event - level textual emotion sensing using mutual action histogram between entities. Expert systems with applications. 37(2), pp. 1643 - 1653.

Lu, C.-H., Jen, H.-S., & Cruz-Lara , S. (2006). Emotion Detection in Textual Information by Semantic Role Labelling and Web Mining Techniques. In Third Taiwanese-French Conference on Information Technology – TFIT. Nancy-France.

Lugmayr, A., Sutinen, E., Suhonen, J., Sedano, C., Hlavacs, & Montero, C. (2016). Serious storytelling – a first definition and review. Multimedia tools and applications, Pp. 1-27.

Mahmoud, A. A. (2014). Using games to promote students’ motivation towards learning English. Al-Quds Open University Journal for Educational & Psychological Research &

Studies, 2(5), pp. 11 -33.

Marsella, S., Gratch, J., & Petta., P. (2015). Computational models of emotion. (Vol. 11). (R. A.

Calvo, Ed.) A Blueprint for Affective Computing-A sourcebook and manual.

Matwin, S., & Sazonova, V. (2012). Direct comparison between support vector machine and multinomial naive Bayes algorithms for medical abstract classification. Journal of the American Medical Informatics Association, 19(5), 917-917.

Maynard, D., Bontcheva, K., & Rout, D. (2012). Challenges in developing opinion mining tools for social media. In proceedings of the NLP can u tag user generated content., (pp. 15-22.).

McGriff, S. J. (2000). Instructional system design (ISD): Using the ADDIE model.

McKay, J., & Marshall, P. (2005). In Proceedings of the 16th Australasian Conference on Information Systems,. Sydney, Australia.: A Review of Design Science in Information Systems.

Medin, D., & Bazerman , M. (1999). Broadening behavioral decision research: multiple levels of cognitive processing. Psychon Bull Review, 6(4), pp. 533–546.

Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.

Miłkowski, M. (2010). Developing an open-source, rule-based proofreading tool. Software:

Practice and Experience, 40(7), 543-566.

Mihalcea, R., & Liu, H. (2006). A corpus-based approach to finding happiness. In Proceedings of the AAAI Spring Symposium on Computational Approaches to Analysing Weblogs (pp.

139–144.). AAAI Press.

Miner, G. (2012). Practical text mining and statistical analysis for non-structured text data applications. Academic Press.

Mitchell, D. (2011). The nexus between decision-making and emotion regulation: a review of convergent neurocognitive substrates. Behaviour brain research, 217, pp. 215–231.

Mohammad, S. M. (2012). Emotional tweets. In Proceedings of the First Joint Conference on Lexical and Computational Semantics, (pp. 246–255,). Montr´eal, Canada.

116

Mohammad, S. M., & Yang, T. W. (2011). Tracking sentiment in mail: How genders differ on emotional axes. In Proceedings of the ACL Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, WASSA ’11. Portland, OR, USA.

Mohzan, A., Hassan, N., & Halil, N. (2012). The emotional intelligence on academic achievement. In proceedings of the international conference of University Learning and teaching, 6, pp. 303 -312.

Moretti, A., McKnight, K., & Salleb-Aouissi, A. (2015). Application of Sentiment and Topic Analysis to Teacher Evaluation Policy in the US. In Proceedings of the 8th International Conference on Educational Data Mining, (pp. 628 -629).

Mott, T. (2010). 1001 Video Games You Must Play Before You Die. London: Quintessence Editions Ltd., p. 615.

Mramba, N., Apiola, M., Kolog, E. A., & Sutinen, E. (2016). Technology for street traders in Tanzania: A design science research approach. African Journal of Science, Technology, Innovation and Development, 8(1), pp. 121-133.

Mulcrone, K. (2012). Detecting Emotion in Text. University of Minnesota–Morris CS Senior Semminar Paper.

Munezero , M., Montero, C., Sutinen, E., & Pajunen, J. (2014). Are They Different? Affect, Feeling, Emotion, Sentiment, and Opinion Detection in Text. 5(2), pp. 111.

Munezero, M., Montero, C., Mozgovoy, M., & Sutinen, E. (2013). Exploiting Sentiment Analysis to Track Emotions in Students’ Learning Diaries. In Proceedings of Koli calling (pp. 145-152.). Koli: ACM.

Munkova, D., Munk, M., & Vozar, M. (2013). Data Pre-processing evaluation for text mining:

Transaction/sequence model. Procedia, 13, 1198-1207.

Nadkarni, P. M., Ohno-Machado, L., & Chapman, W. W. (2011). Natural language processing:

an introduction. Journal of the American Medical Informatics Association, 18(5), pp. 544-551.

Neviarouskaya, A., Prendinger, H., & Ishizuka, M. (2011). Affect analysis model: novel rule-based approach to affect sensing from text. Natural Language Eng., 17, pp. 95–135.

Nwokolo , C., Anyamene , A., Oraegbunam, N., Anyache, E., Okoye, A., & Obineli, A. (2010).

Access to academic advising and counselling of pupils in public primary schools in south east, Nigeria. Literacy Information and Computer Education Journal (LICEJ), 1(2), pp. 131-134.

Ofsted. (2007). Developing social, emotional and behavioural skills in secondary schools.

London: OfSTED.

Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2), pp 1–135.

Pang, B., Lee, L., & Vaithyanathan, S. (2002). Association for Computational Linguistics.

Thumbs up? Sentiment Classification using Machine Learning Techniques. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP),, (pp. 79-86.). Philadelphia,.

Parkinson, B. (2009). What holds emotions together? Meaning and response coordination.

Cognitive Systems Research,, 10, pp 31-47.

Patel, F., & Soni, N. (2012). Text mining: A Brief survey. International Journal of Advanced Computer Research , 2(4).

Paulus, M., & Yu. , A. (2012). Emotion and decision-making: affect-driven belief systems in anxiety and depression. Trends in cognitive sciences , 16(9), 476-483.

117 Payton , J., Weissberg , R., Durlak, J., Dymnicki , A., Taylor, R., Schellinger, K., & et al. (2008).

The positive impact of social and emotional learning for kindergarten to eighth-grade students: Findings from three scientific reviews. Chicago: Collaborative for Academic, Social, and Emotional Learning.

Peffers, K., Tuunanen, T., Gengler, C. E., Rossi, M., Hui, W., Virtanen, V., & Bragge, J. (2006).

The design science research process: a model for producing and presenting information systems research. In Proceedings of the first international conference on design science research in information systems and technology, (pp. 83-106).

Petta, P., & Gratch, J. (2009). Computational models of emotion. (D. S. Scherer, Ed.) Oxford Companion to Emotion and the Affective Sciences, Oxford University Press, Oxford.

Petta, P., & Gratch, J. (2009). Computational models of emotion. (D. S. Scherer, Ed.) Oxford Companion to Emotion and the Affective Sciences, Oxford University Press, Oxford.