TY - GEN
T1 - InvestLens
T2 - 39th IEEE International Conference on Data Engineering Workshops, ICDEW 2023
AU - Tian, Yun
AU - Liu, Jia
AU - Zhang, Xinyi
AU - Yang, Xingsheng
AU - Ke, Zhaoru
AU - Zhang, Chenyang
AU - Liao, Ling
AU - Hong, Suting
AU - Zhang, Haipeng
AU - Li, Quan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Venture capital (VC) plays an important role in the development of Western economies, fostering innovation and renewal in the broader economy and revealing the dynamics of different frontier industries over time. However, discovering information about industry changes through VC data has been a challenge for partners and research scholars. Researchers have applied many statistical and empirical methods to explore trends and network relationships in VC, but they are often unable to explain how entities in such networks evolve, a difficulty created by the large, heterogeneous, and dynamic nature of VC data. To help them identify industry changes, we designed InvestLens, an interactive visual analytics system to explore the VC syndication network. It identifies the overall pattern and dynamic network evolution of VC and reveals the evolution of related industries. Two case studies and interviews with domain experts validate the validity of InvestLens.
AB - Venture capital (VC) plays an important role in the development of Western economies, fostering innovation and renewal in the broader economy and revealing the dynamics of different frontier industries over time. However, discovering information about industry changes through VC data has been a challenge for partners and research scholars. Researchers have applied many statistical and empirical methods to explore trends and network relationships in VC, but they are often unable to explain how entities in such networks evolve, a difficulty created by the large, heterogeneous, and dynamic nature of VC data. To help them identify industry changes, we designed InvestLens, an interactive visual analytics system to explore the VC syndication network. It identifies the overall pattern and dynamic network evolution of VC and reveals the evolution of related industries. Two case studies and interviews with domain experts validate the validity of InvestLens.
KW - dynamic graph visualization
KW - heterogeneous network embedding
KW - venture capital investments
UR - https://www.scopus.com/pages/publications/85163837655
U2 - 10.1109/ICDEW58674.2023.00007
DO - 10.1109/ICDEW58674.2023.00007
M3 - Conference Proceeding
AN - SCOPUS:85163837655
T3 - Proceedings - 2023 IEEE 39th International Conference on Data Engineering Workshops, ICDEW 2023
SP - 12
EP - 19
BT - Proceedings - 2023 IEEE 39th International Conference on Data Engineering Workshops, ICDEW 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 April 2023 through 7 April 2023
ER -