Investigating the Demand for Blockchain Talents in the Recruitment Market: Evidence from Topic Modeling Analysis on Job Postings

Ge, Chunmian; Shi, Haoyue; Jiang, Junhui; Xu, Xiaoying

doi:10.1016/j.im.2021.103513

Cited by 18 publications

(8 citation statements)

References 33 publications

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“…According to Ge et al’s [ 57 ] empirical study, there is a gap in fulfilling the demand for qualified and skilled blockchain workers. In our study, three respondents reported that the technology is difficult to understand and a lack of skilled workers in this field (Respondent 3, 7, and 8).…”

Section: Discussion Of Findingsmentioning

confidence: 99%

Blockchain technology diffusion in tourism: Evidence from early enterprise adopters and innovators

Maythu,

Kwok,

Teh

2024

Heliyon

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Section: Discussion Of Findingsmentioning

confidence: 99%

Blockchain technology diffusion in tourism: Evidence from early enterprise adopters and innovators

Maythu,

Kwok,

Teh

2024

Heliyon

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“…In the analysis of demand characteristics for recruitment information, the main research methods have undergone changes from simple descriptive statistics to exploratory data analysis, and to data mining methods (including text mining methods). In terms of structured feature analysis, reference [4] provides a detailed classification of recruitment advertisements, mainly including five types: end user support personnel, business analysts, trainers, web and interface designers, and technical writers. The article calculates the proportion of each type of position and lists the main job responsibilities, specific technical and other knowledge and skill requirements of each position in the form of text description; In addition, the article provides a detailed frequency statistical analysis of the demand for work experience.…”

Section: Related Workmentioning

confidence: 99%

Research on the Characteristics of Industrial Talent Demand Depending on Big Data Technology

Li Li

2024

jes

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For a long time, there is a mismatch between supply and demand for industrial talents, and it is difficult to achieve a dynamic balance between talent supply and job demand. This paper aims to mine and analyze the characteristics of industrial talent demand through big data technology, so as to provide skills training reference for talent supply and provide talents with high matching degree for job demand. In this paper, TF-IDF is used as a feature selection method to extract highly representative feature words to help distinguish different talent information data to a greater extent. In addition, combined with the construction method of statistical analysis, quantitative indexing analysis of talent information data is carried out, which enhances the expansion of label system and makes talent portraits more precise and accurate. Through the experimental research, it is proved that the research system of industrial talent demand characteristics proposed in this paper can effectively analyze and match the characteristics of industrial talents. Therefore, in the social employment and higher education, we can combine the methods proposed in this paper to assist decision-making, and promote the dynamic balance between the demand and supply of industrial talents.

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“…Ge, C. et al revealed the current status of recruitment of blockchain-related talents and proposed a data-driven approach combining descriptive statistics, thematic modeling, and regression analysis. Based on the above comprehensive methodology analysis, 11 skills required for blockchainrelated jobs were identified [18].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Talent Cultivation Mode of Network and New Media Communication Majors in Colleges and Universities under the Background of Big Data

Yao

2024

Applied Mathematics and Nonlinear Sciences

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In college education, the introduction of data analysis to quantitatively analyze students’ knowledge has become a new trend. The education of network and new media communication majors can also use big data to assist. To this end, this paper uses knowledge tracking technology to construct an auxiliary teaching model for network and new media communication majors in colleges and universities. A new cross-feature formula is used to incorporate many elements of students’ answers into the feature calculation to improve the operation effect of DKVMN model and avoid the complex operation brought by dimensionality reduction. Introducing the cross formula of guessing rate and error rate refreshment based on cognitive diagnostic model. The judgment level of the model is tested using a public dataset after the model has been constructed and put into practical use in a university’s network and new media communication department. Seventy-three students in the department had a good grasp of the knowledge points and six had an excellent understanding. The adjusted means of the experimental and control groups are 93.102 and 82.596 respectively, and there is a significant difference between the two groups of students’ academic performance (p<0.05). The model in this paper can accurately determine the mastery of students’ knowledge points and provide a development direction based on data analysis for teaching network and new media communication majors in colleges and universities.

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Investigating the Demand for Blockchain Talents in the Recruitment Market: Evidence from Topic Modeling Analysis on Job Postings

Cited by 18 publications

References 33 publications

Blockchain technology diffusion in tourism: Evidence from early enterprise adopters and innovators

Blockchain technology diffusion in tourism: Evidence from early enterprise adopters and innovators

Research on the Characteristics of Industrial Talent Demand Depending on Big Data Technology

Analysis of Talent Cultivation Mode of Network and New Media Communication Majors in Colleges and Universities under the Background of Big Data

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