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t-hoarder_kit

(★ 62)

Set of basic tools to extract data from the Twitter API and visualize graphs

파일 탐색기

ZIP 다운로드

- taller_datos.key
- nombres_hombre.csv
- nombres_mujer.csv
- spain_localidades.csv
- spain_provincias.csv
- spain_regions.csv
- stopwords.txt
- t_hoarder_kit.bat
- t_hoarder_kit.sh
- t_hoarder_menu.py
- tsv2csv.py
- twarc2thoarder.py
- tweet_auth.py
- tweet_get_fotos.py
- tweet_rest.py
- tweet_search.py
- tweet_streaming.py
- tweets_add_communities.py
- tweets_classify.py
- tweets_entity.py
- tweets_grafo.py
- tweets_spread.py
- tweets_spread_by_community.py
- tweets_uniq.py
- user_card.py
- user_klout.py
- users_roles.py
- users_types.py
README.md

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Set of basic tools to extract data from the Twitter API and visualize graphs

## Installation

Recommended to clone with git, so versions are automatically updated

git clone https://github.com/congosto/t-hoarder_kit

Dependencies: [tweepy](https://github.com/tweepy/tweepy)

Python 2.7.12 or newer. Python 3.x not supported

---

Could be used as an alternative this [Dropbox Virtual Machine](https://www.dropbox.com/s/j0p26bmgmct3vll/como_instalar_VM_taller_datos_twitter.pdf?dl=0) with all software installed (The VM has a size almost 4 GB so it is recommended to install it from a high speed connection)

If VM is used, reading this use case is recommended [How to use t-hoarder_kit with the Virtual Machine ](http://periodisme-dades.recursos.uoc.edu/es/6-1-4-preguntas-a-resolver/) Includes how to analyze network relationships with gephi

---

## Data enviroment

T-hoarder kit works on the following directory structure

T-hoarder_kit --+-- keys (app keys and users access token for oauth authentication in the API)
                     |
                     +- scripts ( scripts in Python)
                     |
                     +--resources (Some information needed to process data)
                     |
                     +- store -+-- experiment-1 ( A directory for each experiment so the data is not mixed)
                               |
                               +-- experiment-2
                               ....
                               |
                               +-- experiment-n

Assume that the access keys are in the keys directory and the results are deposited in the store/experiment directory

## Execution Environments

### Windows:

- It is required to include an environment variable called t-hoarder_kit_HOME with the directory where it is installed t-hoarder_kit
  - It is needed to add in the PATH environment variable the directory where the t-hoarder_kit scripts have been installed (the content of the environment variable t-hoarder_kit_HOME\scripts)
  - Open a terminal (cmd)
  - Run the command t_hoarder_kit.bat

### Linux

- Open a terminal
  - Run the command t_hoarder_kit.sh

t_hoarder_kit.bat (Windows) and t_hoarder_kit.sh (linux) provide this menu for access to python scripts.

1. Get a user token access
      2. Get users information (profile | followers | following | relations | tweets | h_index)
      3. Make a query on Twitter
      4. Get tweets in real time
      5. Generate the declared relations graph (followers or following or both)
      6. Generate the dynamic relations graph (RT | reply | mentions)
      7. Processing tweets (sort |entities| classify| users | spread)
      8. Exit

For more information, **visit the [wiki](https://github.com/congosto/t-hoarder_kit/wiki)**

Using the python scripts from the command line the keys and the results is free to place them where you want

tweet_auth.py [-h] keys_app user

tweet_rest.py [-h] [--id_user] [--fast]
                     (--profile | --followers | --following | --relations | --connections | --tweets | --h_index)
                     keys_app keys_user file_users

usage: tweet_search.py [-h] [--query QUERY] [--file_out FILE_OUT]
                       [--format FORMAT]
                       keys_app keys_user

tweet_streaming.py [-h] [--users USERS] [--words WORDS]
                          [--locations LOCATIONS]
                          app_keys user_keys dir_out file_dest

tweets_grafo.py [-h] [--top_size TOP_SIZE] (--RT | --mention | --reply)
                       file_in

tweets_entity.py [-h] [--top_size TOP_SIZE] [--TZ TZ]
                        file_in path_experiment path_resources

tweets_classify.py [-h] file_in file_topics path_experiment

users_types.py [-h] file_in path_experiment

tweets_spread.py [-h] [--top_size TOP_SIZE] [--TZ TZ]
                        file_in path_experiment

user_klout.py [-h] file_users APIkey