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1صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s005Test
https://figshare.com/articles/figure/Significant_correlations_i_ps_i_5_3_x_10_sup_5_sup_for_the_Individualising_and_Binding_moral_super-foundations_/24661175Test -
2صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s006Test
https://figshare.com/articles/figure/Feature_importance_for_the_Individualising_and_Binding_moral_super-foundations_/24661181Test -
3صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s009Test
https://figshare.com/articles/figure/Complete_Spearman_correlations_between_MFT_traits_and_pitch_features_/24661193Test -
4صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g001Test
https://figshare.com/articles/figure/Overview_of_methodological_framework_/24661196Test -
5صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s007Test
https://figshare.com/articles/figure/Complete_Spearman_correlations_between_MFT_traits_and_lyrics_features_top_and_middle_panels_and_high-level_music_attributes_bottom_panel_/24661184Test -
6صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s008Test
https://figshare.com/articles/figure/Complete_Spearman_correlations_between_MFT_traits_and_timbre_features_/24661190Test -
7صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g002Test
https://figshare.com/articles/figure/Significant_Spearman_correlations_i_ps_i_5_3_x_10_sup_5_sup_for_Individualising_moral_foundations_/24661199Test -
8صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience العلاقة: https://figshare.com/articles/figure/Feature_importance_for_Binding_moral_foundations_/24661208Test
الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g005Test
https://figshare.com/articles/figure/Feature_importance_for_Binding_moral_foundations_/24661208Test -
9صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g003Test
https://figshare.com/articles/figure/Significant_Spearman_correlations_i_ps_i_5_3_x_10_sup_5_sup_for_Binding_moral_foundations_/24661202Test -
10صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g004Test
https://figshare.com/articles/figure/Feature_importance_for_Individualising_moral_foundations_/24661205Test