scholarly journals Exploring Forest Sector Research Subjects and Trends from 2000 to 2019 Using Topic Modeling

2021 ◽  
Author(s):  
T. Nummelin ◽  
R. Hänninen ◽  
M. Kniivilä
Keyword(s):  
Topic Modeling ◽  
Forest Ecology ◽  
Social Research ◽  
Academic Research ◽  
Policy Decision ◽  
Modeling Method ◽  
Forest Sector ◽  
Global Changes ◽  
Research Subjects ◽  
Sector Research

Abstract Purpose of Review This review aims to discover the most common topics and trends in international scientific forest sector research between January 2000 and December 2019 and to test the suitability of a quantitative topic-modeling method to extract topics from the data. The results will be helpful for both researchers and policy decision-makers in identifying emerging research topics and possible research gaps. The analysis framework covers the complete forest wood chain (FWC) with PESTE factors. PESTE is applied to analyze political, economic, social, technological, and ecological/environmental factors affecting the FWC. Recent findings In the last two decades, forests and the forest sector have been impacted by several global changes, policies, and megatrends. Previous systematic syntheses of forest sector research reveal that economic, policy, and social research have remained underrepresented in the forest sector literature. Research areas related to forest ecology and climate change have been increasing. More recently, growth has also been detected in social aspects especially related to the increasing literature on forest ecosystem services. Results A total of 160 topics were extracted from 14,470 abstracts of 15 leading international peer-reviewed forest science journals. The ecological topics of forest resources and technological topics of industry and products were by far the two largest subject areas. Ecological topics increased, while technological topics slightly decreased, during the period between 2000 and 2019. A clear decline in the share of topics concerning end-product markets was detected. Indeed, changes in end markets drive changes in the entire forest wood chain. To support the goal of a transition from a fossil-based economy to a bioeconomy, it will be important to increase academic research on policy impacts, as well as social and ecological sustainability issues to cover all the stages of the FWC more evenly. The topic-modeling method was a useful tool in data mining, but human intelligence is needed to interpret and classify the topics extracted by this approach.

scholarly journals A Study on the Characteristics of Academic Topics Related to Renewable Energy Using the Structural Topic Modeling and the Weak Signal Concept

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1497
Author(s):  
Chankook Park ◽  
Minkyu Kim
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Topic Modeling ◽  
Academic Research ◽  
High Rate ◽  
Weak Signals ◽  
Energy Potential ◽  
Rate Of Increase ◽  
Probabilistic Topic Modeling ◽  
To Receive

It is important to examine in detail how the distribution of academic research topics related to renewable energy is structured and which topics are likely to receive new attention in the future in order for scientists to contribute to the development of renewable energy. This study uses an advanced probabilistic topic modeling to statistically examine the temporal changes of renewable energy topics by using academic abstracts from 2010–2019 and explores the properties of the topics from the perspective of future signs such as weak signals. As a result, in strong signals, methods for optimally integrating renewable energy into the power grid are paid great attention. In weak signals, interest in large-capacity energy storage systems such as hydrogen, supercapacitors, and compressed air energy storage showed a high rate of increase. In not-strong-but-well-known signals, comprehensive topics have been included, such as renewable energy potential, barriers, and policies. The approach of this study is applicable not only to renewable energy but also to other subjects.

scholarly journals How ethical challenges of covert observations can be met in practice

2021 ◽  
pp. 174701612110082
Author(s):  
Nicole Podschuweit
Keyword(s):  
Social Research ◽  
Role Playing ◽  
Great Distance ◽  
Point Of View ◽  
Ethical Challenges ◽  
Research Subjects ◽  
Written Information ◽  
Ethical Debate ◽  
The People ◽  
Almost All

This paper aims to bring into the ethical debate on covert research two aspects that are neglected to date: the perspective of the research subjects and the special responsibility of investigators towards their observers. Both aspects are falling behind, especially in quantitative social research. From a methodological point of view, quantitative forms of covert observation involve a great distance between the researcher and the research subjects. When human observers are involved, the focus is usually on the reliable application of the measuring instrument. Therefore, herein, a quantitative study is used as an example to show how the protection needs of both the observed persons and the observers can be met in practice. The study involved 40 student observers who covertly captured everyday conversations in real-world settings (e.g. in cafés or trains) by a highly standardised observation scheme. The study suggests that the anonymity of the research subjects and their trust in the observers are crucial for their subsequent consent. However, many participants showed only little or even no interest in the written information they were provided. Further, this study strongly emphasises how mentally stressful covert observations are to the observers. Almost all observers were worried in advance that the people they were observing would prematurely blow their cover and confront them. Role-playing and in-depth discussions in teams are good strategies to alleviate such and other fears and to prepare student assistants well for their demanding work in the field.

scholarly journals Users and Social Science Research: Policy, Problems and Possibilities

1997 ◽  
Vol 2 (3) ◽  
pp. 69-81 ◽  
Author(s):  
B. Rappert
Keyword(s):  
Research Policy ◽  
Social Research ◽  
Public Funding ◽  
Social Science Research ◽  
Academic Research ◽  
User Involvement ◽  
Science Research ◽  
Research Process ◽  
The Uk ◽  
Policy Problems

Recent times have seen a significant reorientation in public funding for academic research across many countries. Public bodies in the UK have been at the forefront of such activities, typically justified in terms of a need to meet the challenges of international competitiveness and improve quality of life. One set of mechanisms advanced for further achieving these goals is the incorporation of users’ needs into various aspects of the research process. This paper examines some of the consequences of greater user involvement in the UK Economic and Social Research Council by drawing on both empirical evidence and more speculative argumentation. In doing so it poses some of the dilemmas for conceptualizing proper user involvement.

scholarly journals Decision-making in Russia’s Foreign Policy Modelling Russia’s Decision-Making with reference to Ukraine and Moldova (2004-2018)

2021 ◽  
Vol 9 (6) ◽  
pp. 42
Author(s):  
Kristine Zaidi
Keyword(s):  
Decision Making ◽  
Foreign Policy ◽  
Academic Research ◽  
Theory Development ◽  
Policy Decision ◽  
Actor Model ◽  
General Applicability ◽  
Proposed Model ◽  
Policy Decision Making

There is a substantial body of literature on Russian foreign policy; however, the decision-making aspect remains comparatively less explored. The ambition of this research developed in two directions; on a practical level, it contributes to knowledge on Russia’s foreign policy decision-making and, on a conceptual plane, to scholarship by way of theory development, underpinning academic research on decision-making in foreign policy. Russia’s decision-making was first viewed through the prism of the Rational Actor Model and Incrementalism; however, their utility was found to be limited. Blended models also did not figure strongly. Through the prism of author’s proposed model of Strategic Incrementalism and its principles, this research demonstrates that Russia’s foreign-policy decision-making is far from a case of ‘muddling through,’ it retains a long-term purposefulness, and that its incremental decisions are guided by farsightedness. The simplicity and general applicability of the model potentially suggest its broader utility.

scholarly journals A Case Study of the Impediments to the Commercialization of Research at the University of Kentucky

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 133
Author(s):  
Nathan L. Vanderford ◽  
Elizabeth Marcinkowski
Keyword(s):  
Academic Research ◽  
Administrative Leadership ◽  
Research Subjects ◽  
University Of Kentucky ◽  
Research Commercialization ◽  
Academic Entrepreneurs ◽  
Number Of Factors ◽  
The University

The commercialization of university-based research occurs to varying degrees between academic institutions. Previous studies have found that multiple barriers can impede the effectiveness and efficiency by which academic research is commercialized. This case study was designed to better understand the impediments to research commercialization at the University of Kentucky via a survey and interview with three successful academic entrepreneurs. The study also garnered insight from the individuals as to how the commercialization process could be improved. Issues with commercialization infrastructure; a lack of emphasis, at the university level, on the importance of research commercialization; a void in an entrepreneurial culture on campus; inhibitory commercialization policies; and a lack of business and commercialization knowledge among faculty were highlighted as the most significant barriers. The research subjects also suggested that commercialization activity may generally increase if a number of factors were mitigated. Such insight can be communicated to the administrative leadership of the commercialization process at the University of Kentucky. Long term, improving university-based research commercialization will allow academic researchers to be more active and successful entrepreneurs such that intellectual property will progress more freely to the marketplace for the benefit of inventors, universities and society.

scholarly journals Forest Sector Research and Development Capacity

2019 ◽  
Author(s):  
Kathleen A Mcginley ◽  
Richard W Guldin ◽  
Frederick W Cubbage
Keyword(s):  
Research And Development ◽  
Forest Sector ◽  
Development Capacity ◽  
Sector Research

The Man With the Leaking Bucket: Ethnography, Journalism, and the Quest for the Transformative Self

2019 ◽  
Vol 20 (6) ◽  
pp. 515-523
Author(s):  
Max Mauro
Keyword(s):  
Social Life ◽  
Social Research ◽  
Academic Research ◽  
Digital Revolution ◽  
Social Sciences And Humanities ◽  
Siegfried Kracauer ◽  
The Status ◽  
Long Time ◽  
German Jewish ◽  
Intellectual Journey

This article looks into the status and identity of ethnography by paying attention to the ideas of transformation and becoming, and to the meanings of “reality” in post postmodern times. Based on a personal reflection about the intellectual journey of the author, and his transition from journalism to academic research, it first provides an illustration of the complicated relationship between journalism, and journalistic practices, with social research during the 20th century. It highlights the trailblazing work of German–Jewish intellectual Siegfried Kracauer during the Weimar years, whose eclectic attention to popular culture and social theory has been for a long time overlooked. Following the postmodern turn, reflexivity has taken center stage in ethnographic methods, but this has not diminished the differences within social sciences and humanities in the way the subject, the researcher, is perceived and interpreted. A contested area of debate remains that of representation, and particularly, the realization that nothing meaningfully exists outside the process of representation. However, this point is further complicated by the status of “reality” in the age of the implosion of social life through the conflation of the private and the public brought about by the digital revolution.

Mathematische Methoden zur Sicherung der Vertraulichkeit und Anonymität von Forschungsdaten / Mathematical Methods to Assure Confidentiality and Anonymity of Research Data

1973 ◽  
Vol 2 (3) ◽  
Author(s):  
Robert F. Boruch ◽  
Günter Endruweit
Keyword(s):  
Social Research ◽  
Legal Protection ◽  
The United States ◽  
Research Data ◽  
Research Subjects ◽  
Mathematical Methods ◽  
Private Lives ◽  
Accuracy And Precision ◽  
The Social ◽  
Response Method

AbstractThe need to develop methods for assuring confidentiality of social research data stems from two related problems. First, research subjects who are emabarassed or threatened by an inquiry about their private lives may refuse to respond or may distort their response, thereby assuring for themselves the confidentiality of particular information; as a consequence, the accuracy and precision of estimates of parameters in social research may be critically undermined. Second, the social researcher in Germany as in the United States, has no legal protection against judicial appropriation of the data for non-research purposes; if obtained from the researcher, the research subjects’ responses may lead to legal or social sanctions against him.The mathematical methods described in this article have been developed to alleviate these problems and, more specifically, to increase the strength of the researcher’s promise that “confidentiality” will be maintained. The randomized response method, the unrelated question method, and the newly developed contamination method permit one to aquire information without needlessly jeopardizing or embarrassing the research subject. The methods, based on simple laws of probability, are summarized and compared in the following remarks.

scholarly journals Exploring Eating Disorder Topics on Twitter: Machine Learning Approach (Preprint)

2020 ◽  
Author(s):  
Sicheng Zhou ◽  
Yunpeng Zhao ◽  
Jiang Bian ◽  
Ann F Haynos ◽  
Rui Zhang
Keyword(s):  
Machine Learning ◽  
Topic Modeling ◽  
Short Term Memory ◽  
Topic Model ◽  
Modeling Method ◽  
Mental Illnesses ◽  
Computational Method ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Domain Expert

BACKGROUND Eating disorders (EDs) are a group of mental illnesses that have an adverse effect on both mental and physical health. As social media platforms (eg, Twitter) have become an important data source for public health research, some studies have qualitatively explored the ways in which EDs are discussed on these platforms. Initial results suggest that such research offers a promising method for further understanding this group of diseases. Nevertheless, an efficient computational method is needed to further identify and analyze tweets relevant to EDs on a larger scale. OBJECTIVE This study aims to develop and validate a machine learning–based classifier to identify tweets related to EDs and to explore factors (ie, topics) related to EDs using a topic modeling method. METHODS We collected potential ED-relevant tweets using keywords from previous studies and annotated these tweets into different groups (ie, ED relevant vs irrelevant and then promotional information vs laypeople discussion). Several supervised machine learning methods, such as convolutional neural network (CNN), long short-term memory (LSTM), support vector machine, and naïve Bayes, were developed and evaluated using annotated data. We used the classifier with the best performance to identify ED-relevant tweets and applied a topic modeling method—Correlation Explanation (CorEx)—to analyze the content of the identified tweets. To validate these machine learning results, we also collected a cohort of ED-relevant tweets on the basis of manually curated rules. RESULTS A total of 123,977 tweets were collected during the set period. We randomly annotated 2219 tweets for developing the machine learning classifiers. We developed a CNN-LSTM classifier to identify ED-relevant tweets published by laypeople in 2 steps: first relevant versus irrelevant (F<sub>1</sub> score=0.89) and then promotional versus published by laypeople (F<sub>1</sub> score=0.90). A total of 40,790 ED-relevant tweets were identified using the CNN-LSTM classifier. We also identified another set of tweets (ie, 17,632 ED-relevant and 83,557 ED-irrelevant tweets) posted by laypeople using manually specified rules. Using CorEx on all ED-relevant tweets, the topic model identified 162 topics. Overall, the coherence rate for topic modeling was 77.07% (1264/1640), indicating a high quality of the produced topics. The topics were further reviewed and analyzed by a domain expert. CONCLUSIONS A developed CNN-LSTM classifier could improve the efficiency of identifying ED-relevant tweets compared with the traditional manual-based method. The CorEx topic model was applied on the tweets identified by the machine learning–based classifier and the traditional manual approach separately. Highly overlapping topics were observed between the 2 cohorts of tweets. The produced topics were further reviewed by a domain expert. Some of the topics identified by the potential ED tweets may provide new avenues for understanding this serious set of disorders.

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