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GMU:Critical VR Lab I/L.-E. Kuehr (view source)
Revision as of 10:19, 5 November 2020
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For the texts to generate the word-clouds, the text of the posts and comments are extracted from the JSON files and are analyzed using the natural language processing technique ''word2vec''. | For the texts to generate the word-clouds, the text of the posts and comments are extracted from the JSON files and are analyzed using the natural language processing technique ''word2vec''. | ||
[[File:VRI-LEK-Epochs.PNG|none|1000px|Learning Process]] | [[File:VRI-LEK-Epochs.PNG|none|1000px|Learning Process]] | ||
The resulting vector space is of very high dimensionality, thus cannot be easily visualized. To reduce the high dimensional space to three | The resulting vector space is of very high dimensionality, thus cannot be easily visualized. To reduce the high dimensional space to three dimensions the method ''t-distributed stochastic neighbor embedding'' is used, which keeps words close together that are close in the high dimensional space. | ||
[[File:VRI-LEK-Graph.png|none|500px|Resulting Graph]] | [[File:VRI-LEK-Graph.png|none|500px|Resulting Graph]] | ||
The resulting data is then imported into unity using a ''csv''-file and for every data-point a billboard-text of the word is generated. This process is repeated for every text. | The resulting data is then imported into unity using a ''csv''-file and for every data-point a billboard-text of the word is generated. This process is repeated for every text. | ||
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Distribution of things in the world should not be totally random and interaction should have consequences. | Distribution of things in the world should not be totally random and interaction should have consequences. | ||
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==Videos== | |||
{{#ev:youtube|DK_HU3QfhTg|735}} | |||
{{#ev:youtube|_ngl4XmXYD8|735}} | |||
{{#ev:youtube|7c2ym-1aKjI|735}} | |||
{{#ev:youtube|mmFLRg5O5zk|735}} | |||
==Media:== | ==Media:== | ||
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[[File:VRI-LEK-6.png|1000px]] | [[File:VRI-LEK-6.png|1000px]] | ||
== | ==Build:== | ||
Proceed with caution! May load for two-three minutes, because of the large word-clud files. Not very optimised due to 30.000+ words beeing rendered. | |||
[https://drive.google.com/file/d/17MF2j1sobrcWl0_eN8dmqjfruaVi6d-A/view?usp=sharing Build] | |||
==Further Reading:== | ==Further Reading:== | ||