https://github.com/do-me/lbsn-dashboard
A location-based social network dashboard for privacy-aware analysis
https://github.com/do-me/lbsn-dashboard
Last synced: 22 days ago
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A location-based social network dashboard for privacy-aware analysis
- Host: GitHub
- URL: https://github.com/do-me/lbsn-dashboard
- Owner: do-me
- License: mit
- Created: 2021-05-07T09:00:33.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2022-05-29T14:16:10.000Z (almost 3 years ago)
- Last Synced: 2025-04-13T13:15:42.215Z (22 days ago)
- Language: JavaScript
- Homepage: https://geo.rocks/lbsndashboard/
- Size: 5.99 MB
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LBSN-Dashboard
[](https://zenodo.org/badge/latestdoi/365174752)
Find the supplementary repo [here](https://github.com/do-me/LBSN-Thesis) or watch the [videos](https://github.com/do-me/LBSN-Thesis/tree/main/videos)!
A location-based social network dashboard for privacy-aware analysis based on [LBSN structure](https://lbsn.vgiscience.org/), a Docker-based Postgres HyperLogLog implementation from Dunkel, Löchner, Krumpe et al. for LBSN analysis. More info [here](https://github.com/do-me/LBSN-Thesis).
**Disclaimer: This is a prototype for research purposes and not thought for production (subject to SQL-injection)!**
## WORKING DEMOS
- [Bonn, NRW, Germany](https://geo.rocks/dashboards/bonn)
- [Waynesboro, VA, USA](https://geo.rocks/dashboards/waynesboro)
## Content
- Backend consisting of Python web framework (fastapi) excluding docker containers from [LBSN structure](https://lbsn.vgiscience.org/)
- Frontend based on Leaflet and Geoman ready-to-deploy with plugin options (e.g. GeoJSON)
## Data
Use my [Fast-Instagram-Scraper](https://github.com/do-me/fast-instagram-scraper) to retrieve Data e.g. from Instagram. It's fast, easy to use and quickly read into the privacy-aware DB.
## How to use
### Preparation
1. Set up LBSN Docker container with pgadmin (good for quickly checking SQL statements but not necessary) and HLL-DB
2. Download some data from any LBSN such as Instagram. If you use [Fast-Instagram-Scraper](https://github.com/do-me/fast-instagram-scraper) you can use lbsntransform to read the data into the DB with the following command, automatically using `instagram-mapping-for-fast-instagram-scraper.py` (thanks and credits to [Alexander Dunkel](https://github.com/Sieboldianus)!)
```
lbsntransform --origin 13 --input_path_url "path/to/data/fast-instagram-scraper/your-area-of-interest" --file_input --dbpassword_output "eX4mP13p455w0Rd" --dbuser_output "postgres" --dbserveraddress_output "127.0.0.1:25432 " --dbname_output "hlldb" --dbformat_output "hll" --dbpassword_hllworker "eX4mP13p455w0Rd" --dbuser_hllworker "postgres" --dbserveraddress_hllworker "127.0.0.1:25432 " --dbname_hllworker "hlldb" --include_lbsn_objects "origin,post" --file_type "json" --mappings_path "/mappings/" --include_lbsn_bases hashtag,place,date,community,latlng
```
---
### Dashboard
3. Clone repo
4. Install Python dependencies
5. Start Docker container with HLL-DB
6. Adjust DB connection details in `main.py`, remove my bounding boxes for Bonn
7. Start backend with `python app.py`
8. Go to localhost:8000
## Contact
For any questions contact [me](mailto:[email protected]) or find me on [my blog](geo.rocks).