scholarly journals A Comparative Study of Spatial and Temporal Preferences for Waterfronts in Wuhan based on Gender Differences in Check-In Behavior

2019 ◽  
Vol 8 (9) ◽  
pp. 413 ◽  
Author(s):  
Wu ◽  
Li ◽  
Ma
Keyword(s):  
Gender Differences ◽  
Social Media ◽  
Geographical Location ◽  
Distribution Characteristics ◽  
Social Media Data ◽  
Men And Women ◽  
Male And Female ◽  
Points Of Interest ◽  
And Gender ◽  
Media Data

The geographical location and check-in frequency of social platform users indicate their personal preferences and intentions for space. On the basis of social media data and gender differences, this study analyzes Weibo users’ preferences and the reasons behind these preferences for the waterfronts of the 21 major lakes within Wuhan’s Third Ring Road, in accordance with users’ check-in behaviors. According to the distribution characteristics of the waterfronts’ points of interest, this study explores the preferences of male and female users for waterfronts and reveals, through the check-in behaviors of Weibo users, the gender differences in the preference and willingness of these users to choose urban waterfronts. Results show that men and women check in significantly more frequently on weekends than on weekdays. Women are more likely than men to check in at waterfronts. Significant differences in time and space exist between male and female users’ preferences for different lakes.

scholarly journals Predicting ethnicity with data on personal names in Russia

2021 ◽  
Author(s):  
Alexey Bessudnov ◽  
Denis Tarasov ◽  
Viacheslav Panasovets ◽  
Veronica Kostenko ◽  
Ivan Smirnov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Ethnic Groups ◽  
Geographical Location ◽  
Ethnic Relations ◽  
Social Media Data ◽  
Personal Names ◽  
Learning Classifier ◽  
Media Data

In this paper we develop a machine learning classifier that predicts perceived ethnicity from data on personal names for major ethnic groups populating Russia. We collect data from VK, the largest Russian social media website. Ethnicity has been determined from languages spoken by users and their geographical location, with the data manually cleaned by crowd workers. The classifier shows the accuracy of 0.82 for a scheme with 24 ethnic groups and 0.92 for 15 aggregated ethnic groups. It can be used for research on ethnicity and ethnic relations in Russia, in particular with VK and other social media data.

scholarly journals USING CROWDSOURCED DATA (TWITTER & FACEBOOK) TO DELINEATE THE ORIGIN AND DESTINATION OF COMMUTERS OF THE GAUTRAIN PUBLIC TRANSIT SYSTEM IN SOUTH AFRICA

2016 ◽  
Vol III-2 ◽  
pp. 143-150 ◽  
Author(s):  
T. Moyo ◽  
W. Musakwa
Keyword(s):  
Social Media ◽  
Prediction Models ◽  
Transit System ◽  
Social Media Data ◽  
Points Of Interest ◽  
Crowdsourced Data ◽  
Data Source ◽  
Media Data ◽  
Inform Decision Making ◽  
Concentration Levels

The study of commuters’ origins and destinations (O_D) promises to assist transportation planners with prediction models to inform decision making. Conventionally O_D surveys are undertaken through travel surveys and traffic counts, however data collection for these surveys has historically proven to be time consuming and having a strain on human resources, thus a need for an alternative data source arises. This study combines the use social media data and geographic information systems in the creation of a model for origin and destination surveys. The model tests the potential of using big data from Echo echo software which contains Twitter and Facebook data obtained from social media users in Gauteng. This data contains geo-location and it is used to determine origin and destination as well as concentration levels of Gautrain commuters. A kriging analysis was performed on the data to determine the O-D and concentration levels of Gautrain users. The results reveal the concentration of Gautrain commuters at various points of interest that is where they work, live or socialise. The results from the study highlight which nodes attract the most commuters and also possible locations for the expansion for Gautrain. Lastly, the study also highlights some weakness of crowdsourced data for informing transportation planning.

Gender Differences in Advanced Mobile Services Acceptance

2016 ◽  
pp. 1718-1736
Author(s):  
Alicia Rodriguez Guirao ◽  
Carolina Lopez Nicolas ◽  
Harry Bouwman
Keyword(s):  
Gender Differences ◽  
Social Media ◽  
Theoretical Model ◽  
Driving Forces ◽  
Mobile Services ◽  
Moderator Variable ◽  
Male And Female ◽  
Media Services ◽  
Critical Issues ◽  
And Gender

By stating that the antecedents of customers´ intentions to use mobile services should be studied across service categories and gender differences, the purpose of this article is to investigate the validity and differential predictive power of a model that explain acceptance of several mobile services across male and female customers. This study contributes to the emerging but limited body of research on consumer adoption of advanced mobile services by addressing several critical issues. First, the present paper focuses on two mobile services, namely m-location and m-social media, as they are considered as the new age of advanced mobile services. Furthermore, we include gender as a moderator variable. A theoretical model is proposed and tested in a sample of 429 Dutch consumers. Results from structural modeling equations show that the factors explaining the acceptance of m-location and m-social media services differ. Second, gender moderating effect has been found significant as gender differences exist in the strength of various paths. In addition to its theoretical contributions, this research presents important practical contributions. In particular, practitioners can gain valuable insights into the driving forces of mobile services.

scholarly journals Psychology of Male and Female Communicative Activity

2008 ◽  
Vol 11 (1) ◽  
pp. 289-300 ◽  
Author(s):  
Svetlana A. Vasyura
Keyword(s):  
Gender Differences ◽  
Empirical Study ◽  
Gender Identity ◽  
Interpersonal Relations ◽  
Empirical Studies ◽  
Men And Women ◽  
Male And Female ◽  
Communication Difficulties ◽  
And Gender ◽  
Communicative Activity

The article features a brief overview of theoretical and empirical studies in communication psychology and sociability of men and women, boys and girls. Russian and foreign studies are summarized to point out that girls and women place greater emphasis on communication and interpersonal relations than do boys and men. Moreover, female communication is more emotional. The article presents the results of the author's own empirical study of male and female communicative activity. Communicative activity is viewed as a complex psychological phenomenon, a degree of the subject's willingness to interact. Communicative activity was studied with the test proposed by the Russian psychologist, Krupnov, and designed to detect the following components of communicative activity: dynamic (natural), emotional, motivational, cognitive, regulatory, productive, and two sorts of communication difficulties (operational and personal). Gender differences in communicative activity are shown on a sample of 480 participants aged 18-40 (240 men and 240 women). The article then describes communicative styles of adolescents (130 boys and 130 girls, aged 19-24). Various communicative styles are featured, including “energetic, businesslike,” “conformal, emotional,” “diplomatic, externally oriented” for boys and “energetic, sociable,” “emotional, difficult,” and “complaisant, expressive” for girls. Every person's individuality and gender identity are shown to impact their communicative style.

scholarly journals Identification Of Multifunctional Urban Activity Centers In Tokyo

2021 ◽  
Vol 14 (2) ◽  
pp. 83-91
Author(s):  
Vadim I. Boratinskii ◽  
Irina S. Tikhotskaya
Keyword(s):  
Social Media ◽  
Complex Method ◽  
Urban Structure ◽  
Distribution Analysis ◽  
Data Types ◽  
Spatial Autoregression ◽  
Social Media Data ◽  
Points Of Interest ◽  
Media Data ◽  
Urban Activity

Identification of urban activity centers is among the most important components of the urban structure study, it is necessary for reasonable planning, regulation of traffic flows and other practical measures. The purpose of this paper is to design a complex method to identify urban activity centers based on different but universal data types. In this study, we used social media data (Twitter) since it guarantees regular updates and does not rely on administrative borders and points of interest database that was considered a 'hard' representation of multifunctional urban activities. A large amount of geotagged tweets was processed by means of statistical modelling (spatial autoregression) and combined with the distribution analysis of points of interest. This allowed to identify the local centers of urban activity within 23 special wards of Tokyo more objectively and precisely than when only based on the social media data. Thereafter, delimitated centers were classified in order to define and describe their main functional and spatial characteristics. As a result of the study, railway transport was identified as the main attraction factor of the urban activity; the modern urban structure of Tokyo was identified and mapped; a new comprehensive method for identification of urban activity centers was developed and five classes of urban activity centers were defined and described.

Greek chemical engineers. Are they static or mobile? Evidence from the national archive of PhD theses

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Evi Sachini ◽  
Konstantinos Sioumalas-Christodoulou ◽  
Charalampos Chrysomallidis ◽  
Galatios Siganos ◽  
Nikolaos Karampekios
Keyword(s):  
Social Media ◽  
Design Methodology ◽  
Geographical Location ◽  
National Archive ◽  
National Data ◽  
Data Set ◽  
Social Media Data ◽  
Content Type ◽  
Bibliometric Databases ◽  
Media Data

Purpose The purpose of this paper is to identify the geographical location of researchers. Design/methodology/approach Combine standard bibliometric databases with social media data. Findings The majority of the population of the sample (71.8%) – Greek chemical engineers – are static. A significant portion of the mobile researchers (28.2%) returned to their country of origin (25.6%). Performing network analysis, the cluster of countries corresponding to the mobile category of researchers is identified and depicted. Originality/value Herein, this study introduce a new, national data set on doctorate holders that will allow multiple bibliometric analyses in the future. Also, this study is among the few (Gendronneau et al., 2019) that combines standard bibliometric databases with social media data. In cases where multiple affiliations per year pose a difficulty in understanding the geographical location of each individual, LinkedIn data were used. The analysis sheds light on a field of science that is not extensively examined in terms of brain circulation. While similar publications focus on physicians (i.e. cardiologists – Dyachenko and Mironenko, 2018), this paper focus on a subset of doctorate holders in engineering.

scholarly journals Gender Differences in Teaching and Research Performance of University Teachers Based on Discrete Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hong Ding
Keyword(s):  
Gender Differences ◽  
Data Analysis ◽  
Research Performance ◽  
Discrete Data ◽  
Men And Women ◽  
Male And Female ◽  
Teaching And Research ◽  
Female Teachers ◽  
Outstanding Teachers ◽  
And Gender

Numerous studies have found that there were obvious differences between men and women in research performance, but there is little analysis on teaching. At the same time, the existing studies did not classify the teacher sample but only analyzed the overall sample. This study takes both teaching and research into account, and the sample teachers from a certain university in China are divided into three groups such as outstanding teachers in teaching, outstanding teachers in research, and weak teachers in both teaching and research through cluster analysis based on the discrete data analysis of teaching and research workload from 2018 to 2020. The gender differences in teaching and research performance of male and female teachers in every group are analyzed. It is found that there are obvious differences between male and female teachers in the three groups. By analyzing the correlation between male and female teaching and research performance and gender, age, education, and degree of three groups, it is also found that there are differences between men and women in the correlation of individual factors such as degree and type of graduation university. Based on the results, this paper provides several policy recommendations.

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