886,582 research outputs found

    Partial Correctness of a Power Algorithm

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    This work continues a formal verification of algorithms written in terms of simple-named complex-valued nominative data [6],[8],[15],[11],[12],[13]. In this paper we present a formalization in the Mizar system [3],[1] of the partial correctness of the algorithm: i := val.1 j := val.2 b := val.3 n := val.4 s := val.5 while (i n) i := i + j s := s * b return s computing the natural n power of given complex number b, where variables i, b, n, s are located as values of a V-valued Function, loc, as: loc/.1 = i, loc/.3 = b, loc/.4 = n and loc/.5 = s, and the constant 1 is located in the location loc/.2 = j (set V represents simple names of considered nominative data [17]).The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2],[4] with partial pre- and post-conditions [14],[16],[7],[5].Institute of Informatics, University of Białystok, PolandGrzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical aspects of computer science, 19(19–32), 1967.Adam Grabowski, Artur Korniłowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576–580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14–17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716–724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur Korniłowicz. Simple-named complex-valued nominative data – definition and basic operations. Formalized Mathematics, 25(3):205–216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59–76, 2018.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149–158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159–164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141–147, 2018. doi:10.2478/forma-2018-0011.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3–6, 2017., pages 237–244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy Świątek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 – Part II, Szklarska Poręba, Poland, September 17–19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176–186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15–18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504–523. CEUR-WS.org, 2017.Artur Korniłowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11–20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19–22, 2013, Revised Selected Papers, pages 355–378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications – 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9–12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117–138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.27218919

    Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election

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    [EN] The mediatisation model in politics assumes that media conveys political messages between parties and citizenship, with the risk of promoting issues that frame the electoral content in terms of competition. These dynamics could distract from the debate of ideas and political policies. However, digital media like Twitter provide direct communication channels between parties, candidates and users. The present research explores Twitter content during an electoral campaign focused on the four issues proposed by Patterson (1980) to assess mediatisation: political, policy, campaign and personal (regarding the candidate). The goal of this research study is to evaluate the degree of mediatisation on Twitter using this typology. The research also evaluates the influence of the issue on retweet volume. The study¿s basis was a 15.8 million-tweet corpus obtained during the 2015 Spanish General Election pre-campaign and campaign. This dataset was analysed using an automatic classification system. The results highlighted a predominance of policy issues during both the pre- campaign and campaign, except for the two televised debates, during which campaign issues were the most prevalent. On the election night, users commented much more on political issues. Finally, the kind of issue most likely to be retweeted was policy issues.This research was supported by the Spanish Ministry of Economy and Competitiveness, with Grants CSO2013-43960-R (Los flujos de comunicación en los procesos de movilización política: medios, blogs y líderes de opinión) and CSO2016-77331-C2-1-R (Estrategias, agendas y discursos en las cibercampañas electorales: medios de comunicación y ciudadanos).Baviera, T.; Calvo, D.; Llorca-Abad, G. (2019). Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election. Journal of International Communication. 25(2):275-300. https://doi.org/10.1080/13216597.2019.1634619S275300252Antonakaki, D., Spiliotopoulos, D., V. Samaras, C., Pratikakis, P., Ioannidis, S., & Fragopoulou, P. (2017). Social media analysis during political turbulence. PLOS ONE, 12(10), e0186836. doi:10.1371/journal.pone.0186836Barberá, P. (2015). Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data. Political Analysis, 23(1), 76-91. doi:10.1093/pan/mpu011Bartholomé, G., Lecheler, S., & de Vreese, C. (2017). Towards A Typology of Conflict Frames. Journalism Studies, 19(12), 1689-1711. doi:10.1080/1461670x.2017.1299033Batrinca, B., & Treleaven, P. C. (2014). Social media analytics: a survey of techniques, tools and platforms. AI & SOCIETY, 30(1), 89-116. doi:10.1007/s00146-014-0549-4Baviera, T., Peris, À., & Cano-Orón, L. (2017). Political candidates in infotainment programmes and their emotional effects on Twitter: an analysis of the 2015 Spanish general elections pre-campaign season. Contemporary Social Science, 14(1), 144-156. doi:10.1080/21582041.2017.1367833BLUMLER, J. G., & KAVANAGH, D. (1999). The Third Age of Political Communication: Influences and Features. Political Communication, 16(3), 209-230. doi:10.1080/105846099198596Bor, S. E. (2013). Using Social Network Sites to Improve Communication Between Political Campaigns and Citizens in the 2012 Election. American Behavioral Scientist, 58(9), 1195-1213. doi:10.1177/0002764213490698Brants, K., & Neijens, P. (1998). The Infotainment of Politics. Political Communication, 15(2), 149-164. doi:10.1080/10584609809342363Burnap, P., Gibson, R., Sloan, L., Southern, R., & Williams, M. (2016). 140 characters to victory?: Using Twitter to predict the UK 2015 General Election. Electoral Studies, 41, 230-233. doi:10.1016/j.electstud.2015.11.017Campos-Domínguez, E. (2017). Twitter y la comunicación política. El Profesional de la Información, 26(5), 785. doi:10.3145/epi.2017.sep.01Campos-Domínguez, E., & Calvo, D. (2017). Electoral campaign on the Internet: Planning, impact and viralization on Twitter during the Spanish general election, 2015. Comunicación y Sociedad, 0(29), 93-116. doi:10.32870/cys.v0i29.6423Ceron, A., & Splendore, S. (2016). From contents to comments: Social TV and perceived pluralism in political talk shows. New Media & Society, 20(2), 659-675. doi:10.1177/1461444816668187Chadwick, A. (2013). The Hybrid Media System. doi:10.1093/acprof:oso/9780199759477.001.0001Conway, B. A., Kenski, K., & Wang, D. (2015). The Rise of Twitter in the Political Campaign: Searching for Intermedia Agenda-Setting Effects in the Presidential Primary. Journal of Computer-Mediated Communication, 20(4), 363-380. doi:10.1111/jcc4.12124Couldry, N., & Hepp, A. (2013). Conceptualizing Mediatization: Contexts, Traditions, Arguments. Communication Theory, 23(3), 191-202. doi:10.1111/comt.12019Dang-Xuan, L., Stieglitz, S., Wladarsch, J., & Neuberger, C. (2013). AN INVESTIGATION OF INFLUENTIALS AND THE ROLE OF SENTIMENT IN POLITICAL COMMUNICATION ON TWITTER DURING ELECTION PERIODS. Information, Communication & Society, 16(5), 795-825. doi:10.1080/1369118x.2013.783608D’heer, E., & Verdegem, P. (2014). Conversations about the elections on Twitter: Towards a structural understanding of Twitter’s relation with the political and the media field. European Journal of Communication, 29(6), 720-734. doi:10.1177/0267323114544866Díaz-Parra, I., & Jover-Báez, J. (2016). Social movements in crisis? From the 15-M movement to the electoral shift in Spain. International Journal of Sociology and Social Policy, 36(9/10), 680-694. doi:10.1108/ijssp-09-2015-0101DiGrazia, J., McKelvey, K., Bollen, J., & Rojas, F. (2013). More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE, 8(11), e79449. doi:10.1371/journal.pone.0079449Felt, M. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data & Society, 3(1), 205395171664582. doi:10.1177/2053951716645828Filer, T., & Fredheim, R. (2016). Popular with the Robots: Accusation and Automation in the Argentine Presidential Elections, 2015. International Journal of Politics, Culture, and Society, 30(3), 259-274. doi:10.1007/s10767-016-9233-7Freelon, D., & Karpf, D. (2014). Of big birds and bayonets: hybrid Twitter interactivity in the 2012 Presidential debates. Information, Communication & Society, 18(4), 390-406. doi:10.1080/1369118x.2014.952659Giglietto, F., & Selva, D. (2014). Second Screen and Participation: A Content Analysis on a Full Season Dataset of Tweets. Journal of Communication, 64(2), 260-277. doi:10.1111/jcom.12085Gil de Zúñiga, H., Garcia-Perdomo, V., & McGregor, S. C. (2015). What Is Second Screening? Exploring Motivations of Second Screen Use and Its Effect on Online Political Participation. Journal of Communication, 65(5), 793-815. doi:10.1111/jcom.12174Grover, P., Kar, A. K., Dwivedi, Y. K., & Janssen, M. (2019). Polarization and acculturation in US Election 2016 outcomes – Can twitter analytics predict changes in voting preferences. Technological Forecasting and Social Change, 145, 438-460. doi:10.1016/j.techfore.2018.09.009Jensen, K. B. (2013). Definitive and Sensitizing Conceptualizations of Mediatization. Communication Theory, 23(3), 203-222. doi:10.1111/comt.12014Jungherr, A. (2014). The Logic of Political Coverage on Twitter: Temporal Dynamics and Content. Journal of Communication, 64(2), 239-259. doi:10.1111/jcom.12087Kalsnes, B., Krumsvik, A. H., & Storsul, T. (2014). Social media as a political backchannel. Aslib Journal of Information Management, 66(3), 313-328. doi:10.1108/ajim-09-2013-0093Lee, K., Palsetia, D., Narayanan, R., Patwary, M. M. A., Agrawal, A., & Choudhary, A. (2011). Twitter Trending Topic Classification. 2011 IEEE 11th International Conference on Data Mining Workshops. doi:10.1109/icdmw.2011.171López García, G., Llorca Abad, G., Valera Ordaz, L., & Peris Blanes, A. (2018). Los debates electorales, ¿el último reducto frente la mediatización? Un estudio de caso de las elecciones generales españolas de 2015. Palabra Clave - Revista de Comunicación, 21(3), 772-797. doi:10.5294/pacla.2018.21.3.6López-Rico, C.-M., & Peris-Blanes, À. (2017). Agenda e imagen de los candidatos de las elecciones generales de 2015 en España en programas televisivos de infoentretenimiento. El Profesional de la Información, 26(4), 611. doi:10.3145/epi.2017.jul.05MAZZOLENI, G., & SCHULZ, W. (1999). «Mediatization» of Politics: A Challenge for Democracy? Political Communication, 16(3), 247-261. doi:10.1080/105846099198613Murthy, D. (2015). Twitter and elections: are tweets, predictive, reactive, or a form of buzz? Information, Communication & Society, 18(7), 816-831. doi:10.1080/1369118x.2015.1006659Russell Neuman, W., Guggenheim, L., Mo Jang, S., & Bae, S. Y. (2014). The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data. Journal of Communication, 64(2), 193-214. doi:10.1111/jcom.12088Orriols, L., & Cordero, G. (2016). The Breakdown of the Spanish Two-Party System: The Upsurge of Podemos and Ciudadanos in the 2015 General Election. South European Society and Politics, 21(4), 469-492. doi:10.1080/13608746.2016.1198454References to the IBEREVAL Workshop ProceedingsRill, S., Reinel, D., Scheidt, J., & Zicari, R. V. (2014). PoliTwi: Early detection of emerging political topics on twitter and the impact on concept-level sentiment analysis. Knowledge-Based Systems, 69, 24-33. doi:10.1016/j.knosys.2014.05.008Rogstad, I. (2016). Is Twitter just rehashing? Intermedia agenda setting between Twitter and mainstream media. Journal of Information Technology & Politics, 13(2), 142-158. doi:10.1080/19331681.2016.1160263Sampedro, V., & Lobera, J. (2014). The Spanish 15-M Movement: a consensual dissent? Journal of Spanish Cultural Studies, 15(1-2), 61-80. doi:10.1080/14636204.2014.938466Shah, D. V., Hanna, A., Bucy, E. P., Lassen, D. S., Van Thomme, J., Bialik, K., … Pevehouse, J. C. W. (2016). Dual Screening During Presidential Debates. American Behavioral Scientist, 60(14), 1816-1843. doi:10.1177/0002764216676245Shao, C., Ciampaglia, G. L., Varol, O., Yang, K.-C., Flammini, A., & Menczer, F. (2018). The spread of low-credibility content by social bots. Nature Communications, 9(1). doi:10.1038/s41467-018-06930-7Stella, M., Ferrara, E., & De Domenico, M. (2018). Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences, 115(49), 12435-12440. doi:10.1073/pnas.1803470115Stier, S., Bleier, A., Lietz, H., & Strohmaier, M. (2018). Election Campaigning on Social Media: Politicians, Audiences, and the Mediation of Political Communication on Facebook and Twitter. Political Communication, 35(1), 50-74. doi:10.1080/10584609.2017.1334728Vaccari, C., Chadwick, A., & O’Loughlin, B. (2015). Dual Screening the Political: Media Events, Social Media, and Citizen Engagement. Journal of Communication, 65(6), 1041-1061. doi:10.1111/jcom.12187Vaccari, C., & Nielsen, R. K. (2013). What Drives Politicians’ Online Popularity? An Analysis of the 2010 U.S. Midterm Elections. Journal of Information Technology & Politics, 10(2), 208-222. doi:10.1080/19331681.2012.758072Vargo, C. J., Guo, L., McCombs, M., & Shaw, D. L. (2014). Network Issue Agendas on Twitter During the 2012 U.S. Presidential Election. Journal of Communication, 64(2), 296-316. doi:10.1111/jcom.12089Vergeer, M., & Franses, P. H. (2015). Live audience responses to live televised election debates: time series analysis of issue salience and party salience on audience behavior. Information, Communication & Society, 19(10), 1390-1410. doi:10.1080/1369118x.2015.1093526Xu, W. W., Sang, Y., Blasiola, S., & Park, H. W. (2014). Predicting Opinion Leaders in Twitter Activism Networks. American Behavioral Scientist, 58(10), 1278-1293. doi:10.1177/000276421452709

    Increasing Children's Character Overt Behaviours by Neuro Pedagogy-Based Play

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    The research aims to improve the character of children aged 4-6 years by implementing the way the individual interacts with the environment. Qualitative research methods were used in this study, where researchers investigated the open behavior of children aged 4-6 years during neuropedagogy-based play, as well as the open behavior of preschool teachers' professional characters in managing play. The participants in this research were 20 children aged 4-6 years and 4 teachers who were chosen deliberately. The results of the study revealed that all the children's overt character behaviors improved after participating in neuropedagogy-based play. There was not a single child who was classified as having open early behavior. On the other hand, preschool teachers consistently demonstrate the implications of their professional behavior. Based on research findings, it is proven that neuro-pedagogy-based play is beneficial for preschool children and teachers. Extrapolated from this interpretation, curriculum designers and teaching practices are informed that neuro pedagogy-based play can strengthen children's character, this is necessary in preparing future generations who can overcome all challenges in the future. Keywords: neuro pedagogy-based play, open character behavior, children aged 4-6 years References: Bandura A (1997) Social Learning Theory. New Jersey: Prentice  Hall, Inc A Paramount Communication Company Englewood Cliff Beibert M. Hanna & Hasellhorn  Marcus (2016). Individual Differences in Moral Development : Does Intelligence Really Affect Children’s Moral Emotion? Department of Education and Human Development. German Institute for International Educational Research, Frankfurt am Main. Germany Bonomo Virginia (2017) Brain-Based Learning Theory. Journal of Education and Human Development, Vol 6 No 1(Online) DOI: 10.15640/jehd.v6n1a3. URL: http://doi.org/10.15640/jehd.v6na3 Bransford J, Brown A, and Cocking, (2000). How People Learn: Brain, Mind and Experience & School. Washington, DC: National Academy Press Budiartati Emmy. Y & Jamaris Martini  (2018) Music Instructional to Develop Character Value for Early Childhood at Fishery Community Tambak Lorok Semarang City. Journal of Non-Formal Education 4, 47-56 Carter R, Aldridge S, Pge M, & Parker S ( 2009 ) The Human Brain Book. New York, NY: DK Publishing Chojak. M (2018) Neuropedagogy as a Scientific Discipline: Interdisciplinary Description of the Theoretical Basis for the Development of a Research  Field. World Academy of Science, Engineering and Technology. International Journal of Education and Pedagogical Science . Vol 12, No 8, 2018 Chudler E.C (2005) Brain Plasticity What is it?. http://www.faculty.washington.edu/chudler/plast.html Collin Gallian & Dixson Hazel. (1993). Integrated Learning Planned Curriculum Unit (Bookshelf tt) Collin. JW (2007) The Neuroscience and Learning. The Journal of Neuroscience Nursing: Journal of The American Association of Neuroscience Nurses, 39 (5) pp 395-400 Dick Walter & Carey Lou (1985). The Systematic Design of Instruction.  Glenview, Illinois, London England: Scoot, Foresman and Company Fogerty Robin (1991). How to Integrate Curricula. Palaline: IRI/Skylight Training and Publishing Inc. p xii Friedman Issac, Grobgeld Etty & Teichman Weinberg Ariela ( 2016). Neuropedagpgy in Teacher Education. The Mofet Institute: International Portal of Teacher Education. Haghigh Maryam (2013). The Effect of Brain Learning on Iranian EFL Learners ‘Achievement and Retain. Procedia-Social and Behavioral Science, vol 70, page 508-516 Hayes, B. Grant & Hagedorn, W. Bryce (2000).” A Case of Character Education.” Journal of Humanistic Counseling, Education and Development 39, (1) 2-4 Henniger L. Mitchel (2013) Teaching Young Children. One Lake Street, Upper Saddle River, USA: Pearson Education Intan Ahmad (2019) Pidato Rektor Wisuda Tahun Akademik 2018-2019. Jakarta: Unversitas Negeri Jakarta, 1-12 Keles Esra & Cepni Salih,(2006 ) Brain and Learning. Journal of Turkish Science Education, Volume 3, Issue 2, December 2006 Lapina SJ & Colombo JA. (2009 )  Proverty and Brain Development During Cilhdhood: An Approach from Cognitive Psychology and Neuroccience. Washsington, DC. Amarivan Psychological Association Likona, Thomas ( 1996) Eleven Principles for Effective Character Education. Journal of Moral Education 25 (1) :93-100 Martini Jamaris (2016) Empowering Logical Mathemetical of the 4-6 Years Old Children through the Neurosensory Instructional Approach. American Journal of Educational Research. Vol 4. No 10, 768-776.  DOI: 10.12691/education4-10-10 Martini Jamaris & Sofia Hartati (2017) The Role of Undergraduate Students ‘Self-Regulation and Its Influence on their Academic Achievements. International Journal of Multidisciplinary and Current Research 5 May/June 2017, 544-552 Martini Jamaris, Edwita & Trisna Mulyeni (2019) Instructional Model Based Neuro Pedagogy for Character Education of the 4-6 Years Old Children. Research Report. Jakarta  LPPM Universitas Negeri Jakarta. Nass L. Martin (2017) The Superego and Moral Development in the Theories of Freud and Piaget. The Psychoanalytic Study of the Child, Volume 21, 1966,Issue1 1. Contribution of Psychoanalysis Theory. http://doi.org/10.1080/00797308. 1966. 11823252 O’Rahilly R, Mueller F ( 2008) Significant Feature in The Early Prenatal Development of The Human Brain.   Annal Of Anatomy Porter Nancy (1972) Kohlberg and Moral Development. Journal of  Moral Education volume 1 1972, Issue2. Publish on line  7 Juli 2016, http://doi.org/10.1080/030572472001­0206 Rushton. Stephen, Rushon - Jualo Anne & larkin Elizabeth (2019) Neuroscience, Play and Early Childhood Education: Connections, Implications and Assessment.  Early Childhood Education Journal 37: 351-361. DOI 10.1007/s10643-009-0359-3 Santrock, W. John (1996 ) Child Development. Chicago: Brown & Benchmark Seravac, Zoran & Jevanovic Jelena ( 2012) Adaptive Neuro-Fizzy Pedagogical Recommender. Expert Systems with Applications. Volume 39, Issue 10. , 9797-9806 Shearer, Banton (2018). Multiple Intelligences in Teaching and Education Lessons Learned from Neuroscience. Journal of Intelligence, Vol 6, No 38; doi: 10.3390/jintellgence6030038 Soldz ,Stephen (1988) The Construction of Meaning: Kagan, Piaget, and Psychoanalysis. Journal of Contemporary Psychotherapy 18 (1) p 46-59 the phenomena of mind.Nature.com/scitable/blog/brain ) Voytek, Brown (2013) Brain Matricts: How measuring brian biology can explain. White E. Rachel (2012) Power of Play. Minnesota: Minnesota Children’s Museum   &nbsp

    Analyzing cultural expatriates' attitudes toward “Englishnization” using dynamic topic modeling

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    [EN] Several Japanese multinational corporations (MNCs) have recently adopted an English-only policy known as “Englishnization”. This study examines the impact of this policy using computer-assisted text analysis to investigate changes in cultural expatriates’ perceptions of Japanese work practices and values over time. Cultural expatriates are a significant but underexplored outcome of globalization. Despite the recent proliferation of studies on the internationalization of Japanese MNCs, few studies have focused on cultural expatriates' perceptions of corporate language policy in social media texts. This study analyzes a corpus of 208 posts from Rakuten, a Japanese MNC, on Glassdoor from 2009 to 2020. The findings suggest that these posts can be divided into three content groups: the threat of a foreign corporate culture, embracing the Rakuten way, and perceptions of leadership and marginalized status. Further, the posts reveal how Rakuten’s corporate language policy, as an instrument of internal internationalization, impacts external internationalization. The dynamics of “Englishnization’’ reveal a pressing issue facing Rakuten: namely, how to balance multinational cohesion with monolingualism and multiculturalism. This paper aims to demonstrate that dynamic topic modeling could enhance our understanding of the manner in which cultural expatriates and the English-only policy affect the internationalization of Japanese MNCs. It contributes to the literature by examining cultural expatriates’ perceptions of Japanese work practices and values from a diachronic perspective.Zhang, Z. (2021). Analyzing cultural expatriates' attitudes toward “Englishnization” using dynamic topic modeling. Journal of Computer-Assisted Linguistic Research. 5(1):1-26. https://doi.org/10.4995/jclr.2021.15909OJS12651Alalwan, Ali Abdallah. 2018. 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