Big Data Collection with Desktop version of loklak wok

A desktop version of loklak wok is now available. The goal of the wok is to enable users to collect and parse data from social services like twitter and enable users, citizen scientists and companies to analyze big data.

The origin of the project is a tweet by @Frank_gamefreak. Thank you!

Please join the development on GitHub:


How to compile and run

  • import required lib by running
  • compile with mvn clean install -Pexecutable-jar
  • run artifact in target dircetory: java -jar wok-desktop-0.0.1-SNAPSHOT-jar-with-all-dependencies.jar
  • stop program with ESC key

To be done

  • The code has been hacked and butchered and is some kind of Frankenstein. It needs cleanup.
  • Font size is hardcoded. How ugly is that?
  • It would be cool to have a project for code shared between Android and Desktop version.
  • The only dependency which can not be resolved via Maven is loklakj. Wouldn’t it be cool to change that?
  • The used font does not seem to support Asian characters.
Big Data Collection with Desktop version of loklak wok

Tweet analytics with loklak and Kibana as a search front-end

You can use Kibana to analyze large amounts of Tweet data as a source for statistical data. Please find more info on

Kibana is a tool to “explore and visualize your data”. It is not actually a search front-end but you can use it as such. Because Kibana is made for elasticsearch, it will instantly fit on loklak without any modification or configuration. Here is what you need to do:


Kibana is pre-configured with default values to attach to an elasticsearch index containing logstash data. We will use a differnt index name than logstash: the loklak index names are ‘messages’ and ‘users’. When the Kibana Settings page is visible in your browser, do:

  • On the ‘Configure an index pattern’ Settings-page of the kibana interface, enter “messages” (without the quotes) in the field “Index name or pattern”.
  • As soon as you typed this in, another field “Time-field name” appears, with a red border and empty. Use the selectbox-arrows on the right side of the empty field to select one entry which is there: “created_at”.
  • Push the ‘Create’ button.

A page with the name “messages” appears and shows all index fields of the loklak messages index. If you want to search the index from Kibana, do:

  • Click on “Discover” in the upper menu bar.
  • You may probably see a page with the headline “No results found”. If your loklak index is not empty, this may be caused by a too tight time range; therefore the next step should solve that:
  • Click on the time picker in the top right corner of the window and select (i.e.) “This month”.
  • A ‘searching’ Message appears, followed with a search result page and a histogram at the top.
  • replace the wild-card symbol ‘*’ in the query input line with a word which you want to search, i.e. ‘fossasia’
  • You can also select a time period using a click-drag over the histogram to narrow the search result.
  • You can click on the field names on the left border to show a field facet. Click on the ‘+’-sign at the facet item to activate the facet.

The remote search to twitter with the twitter scraper is not done using the elasticsearch ‘river’ method to prevent that a user-frontend like Kibana constantly triggers a remote search. Therefore this search method with kibana will not help to enrich your search index with remote search results. This also means that you won’t see any results in Kibana until you searched with the /api/search.json api.

Tweet analytics with loklak and Kibana as a search front-end