A No-Code Platform for Tie Prediction Analysis in Social Media Networks

被引:2
作者
Schoetteler, Sebastian [1 ,2 ]
Laumer, Sven [2 ]
Schuhbauer, Heidi [1 ]
Scheidthauer, Niklas [1 ]
Seeberger, Philipp [1 ]
Miethsam, Benedikt [1 ]
机构
[1] Nuremberg Inst Technol, Fac Comp Sci, Nurnberg, Germany
[2] FAU Erlangen Nuremberg, Scholler Endowed Chair Informat Syst Digitalizat, Nurnberg, Germany
来源
INNOVATION THROUGH INFORMATION SYSTEMS, VOL II: A COLLECTION OF LATEST RESEARCH ON TECHNOLOGY ISSUES | 2021年 / 47卷
关键词
Social media networks; Tie formation concepts; Tie prediction algorithms; Tie prediction analysis platform; Social media analytics; DESIGN SCIENCE RESEARCH; MISSING LINKS; COMMUNITIES; FRAMEWORK; USERS;
D O I
10.1007/978-3-030-86797-3_32
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Conventional methods for tie prediction analysis in social media networks are often code-intensive and encompass complex steps. Against this backdrop, we used design science research to develop a no-code tie prediction analysis platform. Our evaluation indicates that the platform significantly reduces tie prediction analysis complexity and, depending on the network size, also total prediction time. Moreover, it maintains a prediction accuracy similar to that of conventional, code-intensive methods. Thus, our artifact substantially facilitates tie prediction analysis for social media network researchers and practitioners.
引用
收藏
页码:475 / 491
页数:17
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