Linjiang Guo

Master’s student (reading)
Email / Blogs / GitHub /ORCID

👩🏼‍💻 Education Experience

*Master degree * _(Sep 2020 - June 2023(expected))_

Chinese Academy of Sciences

Major in management science and engineering

- Participated in projects of the National Natural Science Foundation of China, such as no.72074205 (Research on the “time, degree and efficiency” of Internet governance from the perspective of big data, support:480,000 RMB)

- Some projects such as pubic opinion detection and think tank research.

*Bachelor* _(Sep 2016 - Jul 2020)_
Shandong University

Major in information management and information system

- I learned some useful math and coding skills. Such as python and C#

- Participated in projects of the Natural Science Foundation of China, including no.71572097 (Research on dynamic matching between open innovation platform model and organizational characteristics: From the perspective of adaptive structural Theory, support:460,000 RMB), no.71904106 (Research on causal path and asymmetric relationship of public opinion and link sharing, support:195,000 RMB)

👩🏼‍💻 Publications

• Modeling and Simulating Online Panic in an Epidemic Complexity System: An Agent-Based Approach(SCI, the first author)
• Study on the Meta analysis of the Relationship Between Enterprise Absorption Capacity and Innovation Performance(CSSCI, the third author)
• A novel multi-task based deep model for sentiment analysis and its application in the post-pandemic era(the first author, under review)

👩🏼‍💻 Fellowships And Awards

• 2016-2017, Shandong University Scholarship (The top 15%)
• 2017-2018, Shandong University Scholarship (The top 5%)
• 2018-2019, Shandong University Scholarship (The top 10%)
• 2020, Outstanding Undergraduate Thesis Award, Shandong University
• 2021, First prize of annual student Academic paper(The first), Institutes of Science and Development(CAS)

👩🏼‍💻 Skills And Interests

Software & Tools

R, python, pytorch, C#, LATEX, Netlogo, GIT, SQL

Natural Language Processing

Sentiment Analysis

I have a good knowledge of various mathematical algorithms for sentiment analysis(text classification)， such as Naive Bayes, CNN, LSTM, and BERT. I have also used PyTorch to implement and fine-tune some deep learning sentiment analyses. My latest paper using the deep sentiment analysis model and empirical experiment is under peer review.

Automatic Summarization

I am familiar with two kinds of automatic summarization techniques, namely, extraction summarization and generation summarization. I fine-tune a Chinese summarization model(\href{https://github.com/downw/summrization}{BART}) based on GBT-3 shows\href{https://arxiv.org/abs/1910.13461}{here}

Agent Based Modelling

In my opinion, agent-based modelling is a good tool to simulate complex social and economic problems. I have built a two-layer network, including emotion and health, to study the emotional impact of the epidemic on people in the context of the Internet. The paper can click here.

Econometric Analysis

I have written some examples of how to use R for panel data regression. These blogs are mainly based on the PLM package for R. These examples include model testing and interpretation of regression results(such as fixed effect, random effect). Blogs are here (in Chinese).

Complex Network

It is one of my current research directions for my degree, and I am currently studying it. I am interested in modeling based on super networks (also called network of networks, multi-layers networks).