ECONOMICS AND COMPUTATION CONFERENCE

Previously Published Papers on "Economics and Computation Conference"

• Lexicon-Based Sentiment Analysis for Stock Movement Prediction

  Authors: Zane Turner, Kevin Labille, Susan Gauch, Keywords: Lexicon, sentiment analysis, stock movement prediction., computational finance. DOI:10.5281/zenodo. Abstract: Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

• Investigation of the Physical Computing in Computational Thinking Practices, Computer Programming Concepts and Self-Efficacy for Crosscutting Ideas in STEM Content Environments

  Authors: Sarantos Psycharis, Keywords: STEM, computational thinking, physical computing, Arduino, Labview, self-efficacy. DOI:10.5281/zenodo. Abstract: Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

• The Analysis of Deceptive and Truthful Speech: A Computational Linguistic Based Method

  Authors: Seham El Kareh, Miramar Etman, Keywords: Egyptian Arabic corpus, computational analysis, deceptive features, forensic linguistics, human perception, truthful features. DOI:10.5281/zenodo.3299393 Abstract: Recently, detecting liars and extracting features which distinguish them from truth-tellers have been the focus of a wide range of disciplines. To the author’s best knowledge, most of the work has been done on facial expressions and body gestures but only few works have been done on the language used by both liars and truth-tellers. This paper sheds light on four axes. The first axis copes with building an audio corpus for deceptive and truthful speech for Egyptian Arabic speakers. The second axis focuses on examining the human perception of lies and proving our need for computational linguistic-based methods to extract features which characterize truthful and deceptive speech. The third axis is concerned with building a linguistic analysis program that could extract from the corpus the inter- and intra-linguistic cues for deceptive and truthful speech. The program built here is based on selected categories from the Linguistic Inquiry and Word Count program. Our results demonstrated that Egyptian Arabic speakers on one hand preferred to use first-person pronouns and present tense compared to the past tense when lying and their lies lacked of second-person pronouns, and on the other hand, when telling the truth, they preferred to use the verbs related to motion and the nouns related to time. The results also showed that there is a need for bigger data to prove the significance of words related to emotions and numbers.

• Influence Analysis of Macroeconomic Parameters on Real Estate Price Variation in Taipei, Taiwan

  Authors: Li Li, Kai-Hsuan Chu, Keywords: Real estate price, least-square, grey correlation, macroeconomics. DOI:10.5281/zenodo.2022047 Abstract: It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

• Teaching Computer Programming to Diverse Students: A Comparative, Mixed-Methods, Classroom Research Study

  Authors: Almudena Konrad, Tomás Galguera, Keywords: Computational thinking, computing education, computer programming curriculum, logic, teaching methods. DOI:10.5281/zenodo.1474992 Abstract: Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

• The Creative Unfolding of “Reduced Descriptive Structures” in Musical Cognition: Technical and Theoretical Insights Based on the OpenMusic and PWGL Long-Term Feedback

  Authors: Jacopo Baboni Schilingi, Keywords: Algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication. DOI:10.5281/zenodo.1474624 Abstract: We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

• Competitor Analysis to Quantify the Benefits and for Different Use of Transport Infrastructure

  Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki, Keywords: Competitor analysis, generalized cost, transport economics, quantitative modelling. DOI:10.5281/zenodo.1314524 Abstract: Different transportation modes have key operational advantages and disadvantages, providing a variety of different transport options to users and passengers. This paper reviews key variables for the competition between air transport and other transport modes. The aim of this paper is to review the competition between air transport and other transport modes, providing results in terms of perceived cost for the users, for destinations high competitiveness for all transport modes. The competitor analysis variables include the cost and time outputs for each transport option, highlighting the level of competitiveness on high demanded Origin-Destination corridors. The case study presents the output of a such analysis for the OD corridor in Greece that connects the Capital city (Athens) with the second largest city (Thessaloniki) and the different transport modes have been considered (air, train, road). Conventional wisdom is to present an easy to handle tool for planners, managers and decision makers towards pricing policy effectiveness and demand attractiveness, appropriate to use for other similar cases.

• DYVELOP Method Implementation for the Research Development in Small and Middle Enterprises

  Authors: Jiří F. Urbánek, David Král, Keywords: Blazons, computational assistance, DYVELOP method, small and middle enterprises. DOI:10.5281/zenodo.1129838 Abstract: Small and Middle Enterprises (SME) have a specific mission, characteristics, and behavior in global business competitive environments. They must respect policy, rules, requirements and standards in all their inherent and outer processes of supply - customer chains and networks. Paper aims and purposes are to introduce computational assistance, which enables us the using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It is providing for SMS´s global environment the capability and profit to achieve its commitment regarding the effectiveness of the quality management system in customer requirements meeting and also the continual improvement of the organization’s and SME´s processes overall performance and efficiency, as well as its societal security via continual planning improvement. DYVELOP model´s maps - the Blazons are able mathematically - graphically express the relationships among entities, actors, and processes, including the discovering and modeling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission – added value analysis. The crisis management of SMEs is obliged to use the cycles for successful coping of crisis situations.  Several times cycling of these cases is a necessary condition for the encompassment of the both the emergency event and the mitigation of organization´s damages. Uninterrupted and continuous cycling process is a good indicator and controlling actor of SME continuity and its sustainable development advanced possibilities.

• Economics of Conflict: Core Economic Dimensions of the Georgian-South Ossetian Context

  Authors: V. Charaia, Keywords: Conflict economics, Georgian economy, international organizations, peace building, S. Ossetian economy. DOI:10.5281/zenodo.1127358 Abstract: This article presents SWOT analysis for Georgian - South Ossetian conflict. The research analyzes socio-economic aspects and considers future prospects for all sides including neighbor countries and regions. Also it includes the possibilities of positive intervention of neighbor countries to solve the conflict or to mitigate its negative results. The main question of the article is: What will it take to award Georgians and South Ossetians with a peace dividend?

• Multi-Objective Evolutionary Computation Based Feature Selection Applied to Behaviour Assessment of Children

  Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco, Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children. DOI:10.5281/zenodo.1125385 Abstract: Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.