Hasil untuk "Social Sciences"

Andrey D. Prjibelski, A. Korobeynikov, A. Lapidus

This chapter explores sequence analysis (SA), which conceives the social world as happening in processes, in series of events experienced by social entities. SA refers to a set of tools used to summarize, represent, and compare sequences — i.e. ordered lists of items. Job careers (succession of job positions) are typical examples of sequences. Various other topics have been studied through SA, such as steps in traditional English dances, country-level adoption of welfare policies over one century, or individual and family time-diaries. Andrew Abbott played a pioneering role in the diffusion of SA. With colleagues, Abbott introduced optimal matching analysis (OMA) in the social sciences, a tool to compare sequences borrowed from computer science and previously adapted to DNA sequences. Abbott’s work on SA was part of a wider methodological thinking on social processes. The chapter then looks at the most common type of sequences in social science: categorical time series — i.e. successions of states with a duration defined on a more or less refined chronological scale.

R. Yin

M. Bronstein, Joan Bruna, Yann LeCun et al.

Many scientific fields study data with an underlying structure that is non-Euclidean. Some examples include social networks in computational social sciences, sensor networks in communications, functional networks in brain imaging, regulatory networks in genetics, and meshed surfaces in computer graphics. In many applications, such geometric data are large and complex (in the case of social networks, on the scale of billions) and are natural targets for machine-learning techniques. In particular, we would like to use deep neural networks, which have recently proven to be powerful tools for a broad range of problems from computer vision, natural-language processing, and audio analysis. However, these tools have been most successful on data with an underlying Euclidean or grid-like structure and in cases where the invariances of these structures are built into networks used to model them.

P. Mongeon, Adèle Paul-Hus

Bibliometric methods are used in multiple fields for a variety of purposes, namely for research evaluation. Most bibliometric analyses have in common their data sources: Thomson Reuters’ Web of Science (WoS) and Elsevier’s Scopus. The objective of this research is to describe the journal coverage of those two databases and to assess whether some field, publishing country and language are over or underrepresented. To do this we compared the coverage of active scholarly journals in WoS (13,605 journals) and Scopus (20,346 journals) with Ulrich’s extensive periodical directory (63,013 journals). Results indicate that the use of either WoS or Scopus for research evaluation may introduce biases that favor Natural Sciences and Engineering as well as Biomedical Research to the detriment of Social Sciences and Arts and Humanities. Similarly, English-language journals are overrepresented to the detriment of other languages. While both databases share these biases, their coverage differs substantially. As a consequence, the results of bibliometric analyses may vary depending on the database used. These results imply that in the context of comparative research evaluation, WoS and Scopus should be used with caution, especially when comparing different fields, institutions, countries or languages. The bibliometric community should continue its efforts to develop methods and indicators that include scientific output that are not covered in WoS or Scopus, such as field-specific and national citation indexes.

Lei Zhang, B. Liu

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online.

M. Newman

C. Ferguson

S. Asch

P. Dasgupta, Ismail Serageldin

R. Kline

Jose M. Cortina

R. Alexander

Kimberly A. Neuendorf

Content analysis is one of the most important but complex research methodologies in the social sciences. In The Content Analysis Guidebook author Kimberly Neuendorf provides an accessible core text for upper-level undergraduates and graduate students across the social sciences. Comprising step-by-step instructions and practical advice, this text unravels the complicated aspects of content analysis. The Content Analysis Guidebook provides readers: • Numerous examples from across the social sciences • Sidebars that describe innovative and wide-ranging content analysis projects, from both academia and commercial research • Pedagogical tools in an easy to understand format

S. Verweij, Chaim Noy

Katie Moon, D. Blackman

Eva Lövbrand, S. Beck, J. Chilvers et al.

G. Arminger, C. Clogg, Michael E. Sobel

Fauzi Mulyono, Awanis Linati Haziroh, Mochammad Eric Suryakencana Wibowo et al.

An electric bike, also known as an e-bike or power bike, could be a sort of bike that employs an electric motor as a control source. This thinks about points to get the relationship between hedonic style, product quality, and word of mouth on buying decisions of electric bikes. This investigation centers on individuals who purchase and utilize electric bikes in Juwana. The sampling technique is non-probability sampling. The data analysis utilized such as validity, reliability, normality, multicollinearity, heteroscedasticity, linear regression, and hypotheses test. The study found that hedonic lifestyle, product quality, and word of mouth influence buying decisions for electric bikes. Keywords: Hedonistic Lifestyle; Product Quality; Word of Mouth; Buying Decision

W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera et al.

The Vehicle Routing Problem (VRP) represents a thoroughly investigated domain within operations research, yielding substantial cost savings in global transportation. The fundamental objective of the VRP is to determine the optimal route plan that minimizes the overall distance traveled. This study employs VRP to address the challenge of distributing fresh agricultural products within retail chains. It introduces an integrated bi-objective VRP model that concurrently optimizes resource allocation, order scheduling, and route planning. The proposed model incorporates two objective functions with the goals of minimizing total distribution costs and ensuring timely product deliveries to retail outlets. Real-world characteristics are integrated to enhance practical applicability. All solution algorithms and the developed VRP model undergo testing using data from one of Sri Lanka's largest retail chains. Numerical experiments showcase the efficiency of the proposed algorithm in solving real-world VRP problems. Moreover, the proposed VRP model achieves a 19% reduction in daily distribution costs, including a 24% saving in fuel costs. This not only provides financial benefits but also contributes to the reduction of the carbon footprint of retail chains. The model ensures on-time deliveries to 95% of retail outlets, which is crucial for maintaining the quality of fresh food. The findings of this study underscore the significant cost savings, enhanced sustainability, and improved quality associated with the efficient distribution of fresh agricultural products within retail chains.

Akono Daniel Florent, Bokanda Ekoko Eric, Bisse Salomon Bertrant et al.

The Ebolowa Municipal Lake (EML) (South Cameroon) in order to identify the early diagenesis processes taking place in the lake and the factors influencing them. To this end, 21 samples were collected. In situ, hydrogen potential, redox potential, conductivity, dissolved oxygen content, and turbidity were measured. In the laboratory, the samples were subjected to mineralogical analysis by X-ray diffraction, geochemical analysis by X-ray fluorescence and ICP-MS, and statistical analysis. The coefficient of variation (Qi) was calculated from the geochemical data. In the water column, OD > 2 mg/L, pH > 7 and Eh < 0 mV. In sediments: pH < 7, Eh values are lower. The contents of 2.08 ≤ TOC ≤ 12.65%. The mineralogical procession consists of quartz, kaolinite, gibbsite, goethite, and siderite. The latter is only present in the EML. The sediments are dominated by SiO2 (60.44–89.47%), Al2O3 (6.55–18.17%), and Fe2O3 (1.15–6.21%). The Qi values range from 0.73 to 2.31. The Mn/Fe ratio values are below 0.40. Qi > 1 for Al, Fe, Mn, Mg, K, Na, P, Ni, Co, Zn, Pb, Cd, Cu, Ba, and V, and Qi < 1 for Si; Qi = 1 for Ca. The hierarchical cluster analysis shows two groups: the first one includes the samples from the central and western parts, while the second one includes those from the eastern and southern parts of the lake. The water column is subject to oxic conditions, while the sediments are anoxic. The rapid consumption of oxygen is due to organic mineralization, which is the main diagenesis observed in the lake. This phenomenon is more accentuated in the western part of the lake.