Founded in Shanghai and began with the TechX summer program established in 2016, X ACADEMY is the largest and most influential interdisciplinary summer program and community in China, lasting 14 days.
- 300+ University Enterprise Cooperation. From MIT, Stanford, Tsinghua University to China Youth Development Foundation, Chinese Academy of Sciences... XA has already established partnerships with hundreds of organizations.
- 42,750,000+ Views. In the past, the articles and content XA published on various platforms have received tens of millions of views.
- 500,000+ Followers. The X ACADEMY media matrix has gained widespread attention on social media platforms such as WeChat, Little Red Book, Instagram, etc.
- 6,000 + Global Alumni. Over the past eight years, alumni of X ACADEMY have spread to every corner of the globe.
The above is all coming from X Acadamy's official website: X ACADEMY 2024 - Future Academy
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Computational Social Science Basics: Learn data handling and machine learning with Python, understand computational social science principles, and gain insights into natural language processing and network science.
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Machine Learning & Network Science: Explore supervised, unsupervised, and reinforcement learning using Scikit-Learn. Analyze network structures and models with Network X, and their applications in health, security, and epidemic forecasting.
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NLP: Master word embedding with Word2vec, train models with Gensim, and analyze text data. Understand sentiment analysis techniques and text mining practices using Python.
- Word frequency analysis: Processed a 16,949-line text file of The Republic using Python to analyze word frequency and extracted and wrote the 100 most frequent words along with their frequency to a file on the hard disk.
- Bigdata processing with chunk method: Utilized the Chunk method to process 6,602,141 tweets about Occupy Wall Street, calculating daily tweet counts and the number of unique users.
- Data visualization: Using publicly available experimental result data, reproduced three figures from the paper - Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science
- Use Google search queries to predict influenza epidemics: I referred to Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012–1014. https://doi.org/10.1038/nature07634.
- Categorize news into trustworthy and untrustworthy categories: I trained three machine learning models (naive bayes classifier based on polynomial distribution, random forest classifier, and feedforward neural network) and compared their accuracy. Finally, I selected the model with the highest accuracy to classify true and false news on unlabeled data.
- Topic: The impact of social participation on the mental health of the elderly - A study taking pension institutions as the participation platform.
- Awards: Third Place and Best Research Question Award in Research Track
- I collaborated with a partner to analyze the supply characteristics of elderly institutions and the demand of the elderly in Shanghai from a geospatial perspective. We empirically explored the impact of social activity participation on the mental health of the elderly using the CHARLS database. I was responsible for the empirical analysis, and the data and code have been uploaded.
- The conclusion is that various types of senior care institutions are mainly concentrated in the central urban areas, the elderly groups in the peripheral urban areas have fewer chances to come into contact with senior care institutions, and the spatial distribution of supply and demand is unbalanced, but there is spatial heterogeneity in the distribution of the three types of institutions, which can complement the demand for senior care to a certain extent. Participation in social activities can improve the mental health of the elderly, and elderly care institutions play a key role in improving the mental health of the elderly.