Proposal of indicators for the structural analysis of scientific articles

This study aims to identify variables and indicators that substantiate the development of rules that focus on the structural analysis of scientific articles. Variables and indicators for structural analysis are derived from hypotheses deduced from editorials in important scientific journals. To exemplify and test the indicators, a structural analysis was conducted of 108 scientific articles published in important journals in the field of Management. The hypotheses were mostly tested in accordance with the idea of estimation statistics. The approach that was developed for the structural analysis of the network of texts innovates by employing network analysis indicators (indegree and outdegree). For this purpose, the text matrix is employed through the identification and encoding of cross-references between sections and subsections of each article under study. For the context in question, the field of Management, twelve rules were developed. The interpretations of the possible values for the indicators, expressed in the form of rules, are applied as directives to less experienced scholars in preparing their scientific articles, and for the generation of information to support activities concerning the classification and analysis of scientific articles.

[1]  Kevin G. Corley,et al.  Publishing in AMJ—Part 7: What's Different about Qualitative Research? , 2012 .

[2]  R. Greenwood,et al.  “P2-Form” Strategic Management: Corporate Practices in Professional Partnerships , 1990 .

[3]  Joshua D. Margolis,et al.  Navigating the Bind of Necessary Evils: Psychological Engagement and the Production of Interpersonally Sensitive Behavior , 2008 .

[4]  Steve J. Kramer,et al.  Academic-Practitioner Collaboration in Management Research: A Case of Cross-Profession Collaboration , 2001 .

[5]  Ted Baker,et al.  It's What You Make of It: Founder Identity and Enacting Strategic Responses to Adversity , 2014 .

[6]  A. Langley Strategies for Theorizing from Process Data , 1999 .

[7]  John W. Creswell,et al.  Research Design: Qualitative, Quantitative, and Mixed Methods Approaches , 2010 .

[8]  Ajai R. Singh,et al.  What Is A Good Editorial? , 2006, Mens sana monographs.

[9]  D. Madigan,et al.  Machine learning and data mining: strategies for hypothesis generation , 2012, Molecular Psychiatry.

[10]  J. Webster,et al.  Teaching Effectiveness in Technology-Mediated Distance Learning , 1997 .

[11]  G. Cumming,et al.  The New Statistics , 2014, Psychological science.

[12]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[13]  Geoffrey B. Duggan,et al.  Text skimming: the process and effectiveness of foraging through text under time pressure. , 2009, Journal of experimental psychology. Applied.

[14]  Rodolphe Durand,et al.  Jules or Jim: Alternative Conformity to Minority Logics , 2011 .

[15]  Yan Zhang,et al.  Publishing in AMJ—Part 5: Crafting the Methods and Results , 2012 .

[16]  S. Parker,et al.  Making the most of structural support: : moderating influence of employees' clarity and negative affect. , 2013 .

[17]  Margaret Cargill,et al.  Writing Scientific Research Articles: Strategy and Steps , 2009 .

[18]  E J Huth Authors, editors, policy makers, and the impact factor. , 2001, Croatian medical journal.

[19]  John F. Sherry,et al.  Speaking of Art as Embodied Imagination: A Multisensory Approach to Understanding Aesthetic Experience , 2003 .

[20]  Kyle J. Mayer,et al.  Publishing in AMJ—Part 4: Grounding Hypotheses , 2011 .

[21]  Hongyi Sun,et al.  Structuring papers for success: Making your paper more like a high impact publication than a desk reject , 2014 .

[22]  José Osvaldo De Sordi,et al.  The Text Matrix as a tool to increase the cohesion of extensive texts , 2016, J. Assoc. Inf. Sci. Technol..