DOCSLIB.ORG

Xerox University Microfilms

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

INFORMATION TO USERS This material was produced from a microfilm copy of the original document. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the original submitted. The following explanation of techniques is provided to help you understand markings or patterns which may appear on this reproduction. I.The sign or "target" for pages apparently lacking from the document photographed is "Missing Page(s)". If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. This may have necessitated cutting thru an image and duplicating adjacent pages to insure you complete continuity. 2. When an image on the film is obliterated with a large round black mark, it is an indication that the photographer suspected that the copy may have moved during exposure and thus caijse a blurred image. You will find a good image of die page in the adjacent frame. 3. When a map, drawing or chart, etif., was part of the material being photographed the photographer followed a definite method in "sectioning" the material. It is customary to begin photoing at the upper left hand corner of a large sheet ang to continue photoing from left to right in equal sections with a small overlap. If necessary, sectioning is continued again — beginning below tf e first row and continuing on until complete. 4. The majority of users indicate that thetextual content is of greatest value, however, a somewhat higher quality reproduction could be made from "photographs" if essential to the understanding of the dissertation. Silver prints of "photographs" may be ordc red at additional charge by writing the Order Department, giving the catalog number, title, author and specific pages you wish reproduced. 5. PLEASE NOTE: Some pages may have indistinct print. Filmed as received. Xerox University Microfilms 300 North Z « b Rood Ann Arbor, Michigan 48106 7S-3073 GLOVER, Erananuel Ablade, 1934- RATIONALE FOR RADICAL INNOVATION IN TOE GHANAIAN EDUCATIONAL SYSTBi IN GENERAL AND ART EDUCATION IN PARTICULAR. The Ohio State University, Ph.D., 1974 Fine Arts Xerox University MicrofilmsAnn , Arbor, Michigan 46106 © Copyright by Emmanuel Ablade Glover 1974 THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED. RATIONALE FOR RADICAL INNOVATION IN THE GHANAIAN EDUCATIONAL SYSTEM IN GENERAL AND ART EDUCATION IN PARTICULAR DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Emmanuel Ablade Glover, N.D.D., A.T.D., M.Ed. ***** The Ohio S ta te U niversity 19 74 Reading Committee: Approved By Dr. Ojo Arewa Dr. R. Norris Dr. Paul R. Klohr Dr. Arthur Efland Adviser Division of Art Education ACKNOWLEDGEMENTS I express my thanks to my Academic Adviser, Professor Arthur Efland, first and foremost, for his understanding of my peculiar situation and problems. His tactful criticism and sympathetic encouragement were my consolation through those difficult times when I was being asked to return home, even though I was in the middle of the course. For these, and all his other endearing qualities 1 find myself most indebted; I wish to put on record that appreciation here. I also thank Professor Kenneth Marantz, for giving me the opportunity at all to enter the programme; and my reading committee, Dr. Ojo Arewa, Dr. Paul R. Klohr, and Dr. R. Norris, for their cooperation and understanding. I also thank Miss Ruth Erlandson of The Ohio State University Library for her enthusiasm to guide me through the many bibliographical listings. Above a ll, I owe everything to my mother, Omanyeyoo, who built the foundations for this, and the tasks ahead; to her this dissertation is most affectionately dedicated. i i VITA August 1, 1934 Bom, Lebedi-Accra, Ghana 1962 N.D.D., Central School of Art and Design, London, England 1963-1964 Art Instructor, Winneba Training College, Winneba, Ghana 1965 A.T.D., University of Newcastle-On-Tyne, England 1971 M.Ed., Kent State University, Kent, Ohio 1965 to Present Lecturer, University of Science and Technology, Kumasi, Ghana PUBLICATIONS Adinhra Symbolism, Chart—1968, Stool Symbolism, Chart—1969, Linguist Staff Symbolism, Chart—1969. Published by the Glo Art G allery , Accra, Ghana. FIELD OF STUDY Major Field: Art Education H i \ TABLE OF CONTENTS Page ACKNOWLEDGMENTS................................................................................................ 11 VITA .................................................................................................... i l l LIST OF TABLES AND DIAGRAMS.............................. vi INTRODUCTION.................................................................................................... 1 C hapter I . BACKGROUND OF THE STUDY............................................................. 5 Identification of the Problem Meaning and Depth of this Cultural Decline Inculcating the Culture Through Art I I . HISTORICAL BACKGROUND................................................................. 22 An H is to ric a l Review o f Ghana Education—Traditional Development of Modern Education Education Administration International Schools The College of Art—University of Science and Technology I I I . IDENTIFYING CHRISTIANITY WITH THE PROBLEM....................... 69 The C h ristia n Role The Elite (Christian) Character Review of Current Newspaper Concerns IV. DEDUCTIVE INFERENCES ................................................................. 89 V. REVIEW AND RECOMMENDATIONS.................................................... 99 iv Page APPENDIX A. Teaching Service Decree—N.R.C.D. 247 ........ 114 B. New Proposals for Education.................................................. 124 BIBLIOGRAPHY................................................................................................. 129 v LIST OF TABLES Page Student Distribution By Courses—College of Art ......................... 65 Literacy By Language (In Uhich Literate) Urban/Rural Adult Only ....................................................................... 66 Literacy By Language (In Which Literate) Sex and Major T rib e ................................................................................ 67 C h r i s t i a n s ..................................... 68 LIST OF DIAGRAMS Ethnic Distribution ....................................................... 25 Ghana Regional A dm inistrative Units .................................................. 59 v i INTRODUCTION Ghana* as a nation has all the problems of development. When this former British colony gained her Independence In 1957 the world acclaimed her as one of the most promising nations in Black Africa. But the road had not been rosy, if anything it has been particularly rough all the way. The political party that led the nation into independence adopted an adulterated version of the Biblical philosophy as the war cry: "Seek ye first the political kingdom, and all things shall be added unto you." Political independence has been a reality for seven­ teen years but genuine independence which was hoped for, involving both economic and cultural factors has been extremely illusive. The search for self-realization as a people has been intensified in recent times and many level headed Ghanaians are beginning to ask if independence in the full sense of the term is a realizable aim. To consider whether independence was worth the price or not is slipping back into slave mentality. The question is irrelevant, dependent or independent; because there is no turning back. There is evidence to support the fact that since the arrival of colonlalization we have not found our *Ghana was formerly Gold Coast, a West A frican B ritish colony since 1847. After independence on March 6, 1957, she adopted the name Ghana, which was an ancient West African kingdom. 1 feet as a people.^ Our present woes therefore can be Identified with colonialism or the period that embraces it. This study will endeavour to examine this period making comparison with the era before it so as to deduce its impact on traditional life patterns to help in the search for the basis of Ghana's trouble. The tendency in recent times Is to heap the blame of our woes on the "colonialists," "im perialists," and "neo-colonialists" without first stopping to examine rationally the causes of our predicament. What needs to be done perhaps is to examine sanely and rationally the position today so as to be able to pin-point with some accuracy the causes of the downward trend in national affairs. Such a diagnosis may contribute to the finding of the necessary remedies. This study will attempt to formulate some rationale for such considerations. The task is not in fact as wide and unwieldly as it may sound. Indeed recent high level public pronouncements trace the entire affair to the doors of our educational system. This cannot be said to be un­ reasonable. Dr. E. Evans-Anfom, Chairman of the National Council for Higher Education and Research, in an article entitled "Change Colonial Education," appealed to the country's educational authorities to change the "white-collar" pattern of education inherited from the British into a viable vocational, technical, and professional training system.3 He pointed out that the main draw-back of the colonial curriculum was ^People: It needs to be emphasized though that Ghana was not one nation before the arrival of the European, nonetheless, it is a fact that in their splinter
Recommended publications
  • Scikit-Network Documentation Release 0.24.0 Bertrand Charpentier

    Scikit-Network Documentation Release 0.24.0 Bertrand Charpentier

    scikit-network Documentation Release 0.24.0 Bertrand Charpentier Jul 27, 2021 GETTING STARTED 1 Resources 3 2 Quick Start 5 3 Citing 7 Index 205 i ii scikit-network Documentation, Release 0.24.0 Python package for the analysis of large graphs: • Memory-efficient representation as sparse matrices in the CSR formatof scipy • Fast algorithms • Simple API inspired by scikit-learn GETTING STARTED 1 scikit-network Documentation, Release 0.24.0 2 GETTING STARTED CHAPTER ONE RESOURCES • Free software: BSD license • GitHub: https://github.com/sknetwork-team/scikit-network • Documentation: https://scikit-network.readthedocs.io 3 scikit-network Documentation, Release 0.24.0 4 Chapter 1. Resources CHAPTER TWO QUICK START Install scikit-network: $ pip install scikit-network Import scikit-network in a Python project: import sknetwork as skn See examples in the tutorials; the notebooks are available here. 5 scikit-network Documentation, Release 0.24.0 6 Chapter 2. Quick Start CHAPTER THREE CITING If you want to cite scikit-network, please refer to the publication in the Journal of Machine Learning Research: @article{JMLR:v21:20-412, author= {Thomas Bonald and Nathan de Lara and Quentin Lutz and Bertrand Charpentier}, title= {Scikit-network: Graph Analysis in Python}, journal= {Journal of Machine Learning Research}, year={2020}, volume={21}, number={185}, pages={1-6}, url= {http://jmlr.org/papers/v21/20-412.html} } scikit-network is an open-source python package for the analysis of large graphs. 3.1 Installation To install scikit-network, run this command in your terminal: $ pip install scikit-network If you don’t have pip installed, this Python installation guide can guide you through the process.
  • VIRAL ART Exhibition Guide

    VIRAL ART Exhibition Guide

    VIRAL ART Exhibition Guide VIRAL ART is an exhibition focusing on this last year and the universal pandemic (COVID-19) which has affected many different aspects of life, one of which is evident in the artistic world. COVID-19 has forced many artists to open up to new avenues of expression in many different disciplines; visual art, music, performing arts, photography, fashion, and literature. Some of the main goals for our exhibition are to bring light to how the pandemic has affected all corners of life, especially in regard to artistic capability/expression, and further, illustrate how certain artists captured the essence and experience of COVID-19. Introduction by Taylor Weaver I wanted to start by saying how grateful I am to have been able to lead this exhibition project with the help of Mirea Suarez. I am so proud of each and every one of the girls and hope you can see how hard they have all worked to make this possible. So welcome to our exhibition which we have titled Viral Art! I would like to note that some of the pieces, such as music are slightly more interactive, for example one of the music pieces is a live DJ set and is an hour and a half in total in the event you are interested in watching more – we will only briefly show certain pieces We would like to preface this exhibition by giving a small dedication to those whose lives have been affected by COVID-19. We thought it would be most appropriate to say a few words to front line workers such as those in the healthcare industry who have dedicated their lives to fighting this virus, essential workers such as those in the food (and or) agriculture industry who prepared meals for those in need during these stressful times, Research Methods Fall 2020 Taylor Weaver, Mirea Suarez, Cristina Ponce de Leon, Sophie Schaesberg, Sydney Levno, Annamaria Borvice, Marta Belogolova VIRAL ART Exhibition Guide volunteers, and of course, to all who lost their lives to COVID-19 or people who have lost family members.
  • A Survey of Results on Mobile Phone Datasets Analysis

    A Survey of Results on Mobile Phone Datasets Analysis

    Blondel et al. RESEARCH A survey of results on mobile phone datasets analysis Vincent D Blondel1*, Adeline Decuyper1 and Gautier Krings1,2 *Correspondence: [email protected] Abstract 1Department of Applied Mathematics, Universit´e In this paper, we review some advances made recently in the study of mobile catholique de Louvain, Avenue phone datasets. This area of research has emerged a decade ago, with the Georges Lemaitre, 4, 1348 increasing availability of large-scale anonymized datasets, and has grown into a Louvain-La-Neuve, Belgium Full list of author information is stand-alone topic. We will survey the contributions made so far on the social available at the end of the article networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues. Keywords: mobile phone datasets; big data analysis 1 Introduction As the Internet has been the technological breakthrough of the ’90s, mobile phones have changed our communication habits in the first decade of the twenty-first cen- tury. In a few years, the world coverage of mobile phone subscriptions has raised from 12% of the world population in 2000 up to 96% in 2014 – 6.8 billion subscribers – corresponding to a penetration of 128% in the developed world and 90% in de- veloping countries [1]. Mobile communication has initiated the decline of landline use – decreasing both in developing and developed world since 2005 – and allows people to be connected even in the most remote places of the world. In short, mobile phones are ubiquitous.
  • Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large

    Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large

    Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks Raghvendra Mall, Rocco Langone and Johan A.K. Suykens Department of Electrical Engineering, KU Leuven, ESAT-STADIUS, Kasteelpark Arenberg,10 B-3001 Leuven, Belgium {raghvendra.mall,rocco.langone,johan.suykens}@esat.kuleuven.be Abstract Kernel spectral clustering corresponds to a weighted kernel principal compo- nent analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a repre- sentative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is de- termined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community de- arXiv:1411.7640v2 [cs.SI] 2 Dec 2014 tection techniques like the Louvain, OSLOM and Infomap methods. We show a major advantage our proposed approach i.e. the ability to locate good quality clusters at both the coarser and finer levels of hierarchy using internal cluster quality metrics on 7 real-life networks.
  • Fast Community Detection Using Local Neighbourhood Search

    Fast Community Detection Using Local Neighbourhood Search

    Fast community detection using local neighbourhood search Arnaud Browet,∗ P.-A. Absil, and Paul Van Dooren Universit´ecatholique de Louvain Department of Mathematical Engineering, Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM) Av. Georges Lema^ıtre 4-6, B-1348 Louvain-la-Neuve, Belgium. (Dated: August 30, 2013) Communities play a crucial role to describe and analyse modern networks. However, the size of those networks has grown tremendously with the increase of computational power and data storage. While various methods have been developed to extract community structures, their computational cost or the difficulty to parallelize existing algorithms make partitioning real networks into commu- nities a challenging problem. In this paper, we propose to alter an efficient algorithm, the Louvain method, such that communities are defined as the connected components of a tree-like assignment graph. Within this framework, we precisely describe the different steps of our algorithm and demon- strate its highly parallelizable nature. We then show that despite its simplicity, our algorithm has a partitioning quality similar to the original method on benchmark graphs and even outperforms other algorithms. We also show that, even on a single processor, our method is much faster and allows the analysis of very large networks. PACS numbers: 89.75.Fb, 05.10.-a, 89.65.-s INTRODUCTION ity is encoded in the edge weight, this task is known in graph theory as community detection and has been introduced by Newman [9]. Community detection has Over the years, the evolution of information and com- already proven to be of great interest in many different munication technology in science and industry has had research areas such as epidemiology [10], influence and a significant impact on how collected data are being spread of information over social networks [11, 12], anal- used to understand and analyse complex phenomena [1].
  • A Survey of Results on Mobile Phone Datasets Analysis

    A Survey of Results on Mobile Phone Datasets Analysis

    Blondel et al. EPJ Data Science (2015)4:10 DOI 10.1140/epjds/s13688-015-0046-0 R E V I E W Open Access A survey of results on mobile phone datasets analysis Vincent D Blondel1*, Adeline Decuyper1 and Gautier Krings1,2 *Correspondence: [email protected] Abstract 1Department of Applied Mathematics, Université catholique In this paper, we review some advances made recently in the study of mobile phone de Louvain, Avenue Georges datasets. This area of research has emerged a decade ago, with the increasing Lemaitre, 4, Louvain-La-Neuve, availability of large-scale anonymized datasets, and has grown into a stand-alone 1348, Belgium Full list of author information is topic. We survey the contributions made so far on the social networks that can be available at the end of the article constructed with such data, the study of personal mobility, geographical partitioning, urban planning,andhelp towards development as well as security and privacy issues. Keywords: mobile phone datasets; big data analysis; data mining; social networks; temporal networks; geographical networks 1 Introduction As the Internet has been the technological breakthrough of the ’s, mobile phones have changed our communication habits in the first decade of the twenty-first century. In a few years, the world coverage of mobile phone subscriptions has raised from % of the world population in up to % in - . billion subscribers - corresponding to a penetration of % in the developed world and % in developing countries []. Mobile communication has initiated the decline of landline use - decreasing both in developing and developed world since - and allows people to be connected even in the most remote places of the world.
  • Generalized Louvain Method for Community Detection in Large Networks

    Generalized Louvain Method for Community Detection in Large Networks

    Generalized Louvain method for community detection in large networks Pasquale De Meo∗, Emilio Ferrarax, Giacomo Fiumara∗, Alessandro Provetti∗,∗∗ ∗Dept. of Physics, Informatics Section. xDept. of Mathematics. University of Messina, Italy. ∗∗Oxford-Man Institute, University of Oxford, UK. fpdemeo, eferrara, gfiumara, [email protected] Abstract—In this paper we present a novel strategy to a novel measure of edge centrality, in order to rank all discover the community structure of (possibly, large) networks. the edges of the network with respect to their proclivity This approach is based on the well-know concept of network to propagate information through the network itself; iii) modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ-paths. its computational cost is low, making it feasible even for This technique allows to efficiently compute a edge ranking large network analysis; iv) it is able to produce reliable in large networks in near linear time. Once the centrality results, even if compared with those calculated by using ranking is calculated, the algorithm computes the pairwise more complex techniques, when this is possible; in fact, proximity between nodes of the network. Finally, it discovers because of the computational constraints, the adoption of the community structure adopting a strategy inspired by the well-known state-of-the-art Louvain method (henceforth, LM), some existing techniques is not viable when considering efficiently maximizing the network modularity. The experi- large networks, and their application is only limited to small ments we carried out show that our algorithm outperforms case-studies. other techniques and slightly improves results of the original This paper is organized as follows: in the next Section we LM, providing reliable results.
  • Principles of Tissue Fractionation

    Principles of Tissue Fractionation

    1. Theoret. Biol. (1964) 6, 33-59 Principles of Tissue Fractionation CHRISTIAN DE DUVE Laboratory of Physiological Chemistry University of Louvain, Belgium and The Rockefeiler Institute, New York, N. Y., U.S.A. (Received 15 April 1963) This paper representsan attempt to develop logically the basic premises that tissuefractionation is : (a) a chemical method to be conducted according to the ground rules which govern chemical fractionation in general; (b) potentially applicable to the separationand characterization of all elements of cellular organization, whether known or unknown, which are not irretrievably lost in the initial grinding of the cells. It is shownthat the approach which best answersthese prerequisites is a purely analytical one, untrammeled by any preconceivedidea of the cyto- logical composition of the isolated fractions, and allowing their bio- chemicalproperties to be expressedas continuous functions of the physical parameterwhich determinesthe behaviour of subcellularcomponents in the fractionation systemchosen, Examples are given which illustrate the appli- cation of density gradient centrifugation in this type of approach, as well as the advantageswhich can be derived from the useof mediaof different composition. The resultsof suchexperiments are expressedin the form of distribution curves of biochemical constituents, as with other fractionation methods such as chromatography or electrophoresis,but with the differencethat the independent variable is related to a property, not of the constituent but of its host-particles. These curves can be taken to represent the mass distribution of the particles themselvesif the constituent is assumedto be homogeneouslydistributed amongstthem (postulateof biochemicalhomo- geneity). This assumptionhas been verified for a number of enzymes,which provide valuable markers to fix the position of their host-particleson the distribution diagrams.
  • Female Morbidity and Mortality in Sub-Saharan Africa

    Female Morbidity and Mortality in Sub-Saharan Africa

    INSTITUTE OF MEDICINE IDRC - Lily. IN HER LIFETIME Female Morbidity and Mortality in Sub-Saharan Africa Committee to Study Female Morbidity and Mortality in Sub-Saharan Africa Christopher P. Howson, Polly F. Harrison, Dana Hotra, and Maureen Law, Editors Board on International Health INSTITUTE OF MEDICINE '`moo ,1./'f' `Q T " it',, \: rn NATIONAL ACADEMY PRESS Washington, D.C. 1996 h n NATIONAL ACADEMY PRESS 2101 Constitution Avenue., N.W. Washington, D.C. 20418 NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance. This report has been reviewed by a group other than the authors according to procedures approved by a Report Review Committee consisting of members of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The Institute of Medicine was chartered in 1970 by the National Academy of Sciences to enlist distinguished members of the appropriate professions in the examination of policy matters pertaining to the health of the public. In this the Institute acts under the Academy's 1863 congressional charter responsibility to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Kenneth I. Shine is President of the Institute of Medicine.
  • A Weight-Based Information Filtration Algorithm for Stock-Correlation Networks

    A Weight-Based Information Filtration Algorithm for Stock-Correlation Networks

    A Weight-based Information Filtration Algorithm for Stock-Correlation Networks Seyed Soheil Hosseini, Nick Wormald ∗, and Tianhai Tian School of Mathematics, Monash University Abstract Several algorithms have been proposed to filter information on a complete graph of corre- lations across stocks to build a stock-correlation network. Among them the planar maximally filtered graph (PMFG) algorithm uses 3n − 6 edges to build a graph whose features include a high frequency of small cliques and a good clustering of stocks. We propose a new algo- rithm which we call proportional degree (PD) to filter information on the complete graph of normalised mutual information (NMI) across stocks. Our results show that the PD algorithm produces a network showing better homogeneity with respect to cliques, as compared to eco- nomic sectoral classification than its PMFG counterpart. We also show that the partition of the PD network obtained through normalised spectral clustering (NSC) agrees better with the NSC of the complete graph than the corresponding one obtained from PMFG. Finally, we show that the clusters in the PD network are more robust with respect to the removal of random sets of edges than those in the PMFG network. Key words— stock-correlation network, PD network, PMFG network, normalised mutual in- formation arXiv:1904.06007v1 [q-fin.ST] 12 Apr 2019 1 Introduction ‘Complex systems’ is the term referring to the study of systems with a significant number of com- ponents in which we want to find out how the relationships between those components affect the behaviour of the system. The study of complex systems includes concepts from various disciplines such as mathematics, statistics, and computer science.
  • Community Detection Problem Based on Polarization Measures: an Application to Twitter: the COVID-19 Case in Spain

    Community Detection Problem Based on Polarization Measures: an Application to Twitter: the COVID-19 Case in Spain

    mathematics Article Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain Inmaculada Gutiérrez 1,* , Juan Antonio Guevara 1 , Daniel Gómez 1,2 , Javier Castro 1,2 and Rosa Espínola 1,2 1 Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain; [email protected] (J.A.G.); [email protected] (D.G.); [email protected] (J.C.); [email protected] (R.E.) 2 Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain * Correspondence: [email protected] Abstract: In this paper, we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the risk of polarization. Particularly, we are interested in dealing with the problem of taking into account the polarization of nodes in the community detection problem. Adding this type of information to the community detection problem makes it more realistic, as a community is more likely to be defined if the corresponding elements are willing to maintain a peaceful dialogue. The polarization capacity is modeled by a fuzzy measure based on the JDJpol measure of polarization related to two poles. We also present an efficient algorithm for finding groups whose elements are no polarized. Hereafter, we work in a real case. It is a network obtained from Twitter, concerning the political position against the Spanish government taken by Citation: Gutiérrez, I.; Guevara, J.A.; several influential users. We analyze how the partitions obtained change when some additional Gómez, D.; Castro, J.; Espínola, R.
  • Linear Algebraic Louvain Method in Python

    Linear Algebraic Louvain Method in Python

    c c 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. 1 Linear Algebraic Louvain Method in Python Tze Meng Low, Daniele G. Spampinato Scott McMillan Michel Pelletier Electrical and Computer Engineering Department Software Engineering Institute Graphegon, Inc. Carnegie Mellon University Carnegie Mellon University Portland, OR, USA Pittsburgh, PA, USA Pittsburgh, PA, USA [email protected] [email protected], [email protected] [email protected] Abstract—We show that a linear algebraic formulation of Step 2) A new graph is created from the newly par- • the Louvain method for community detection can be derived titioned graph. Identified communities form the set of systematically from the linear algebraic definition of modularity. new vertices, and edges between vertices in different Using the pygraphblas interface, a high-level Python wrapper for the GraphBLAS C Application Programming Interface (API), we communities are aggregated into a new set of edges. Step demonstrate that the linear algebraic formulation of the Louvain 1 is then applied to this newly created graph. method can be rapidly implemented. The two steps above are repeated until no further improvement Index Terms—Louvain Method, Community Detection, Graph in modularity is obtained. Algorithms, GraphBLAS A. Definition of Modularity I. INTRODUCTION Modularity is a scalar measure used to quantify the strengh Community detection is a critical component in the anal- of community structures within a graph [3].