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Brands_​lyrics_​analysis

TOPIC EXTRACTION AND ANALYSIS OF ALL THESONGS USED BY CROCS, GYMSHARK ANDTARGETThe result of k-mean optimization indicate that the recommended number oftopics is 80, in which i believe is a case of over fitting, because it is 77topics out of 18 unique songs=> which led me to believe that brands use a wide range of song that fitstheir purpose.But, when boiled down to 2 topic, it might indicate that these are wordsmost commonly used in POP(Softcore) and HIP-HOP/RAP(Hardcore)This could be verified by some of the artist in the list, Post Malone,Kendrick Lamar, Juice WRLD VARIABLES RELATIONSHIPS- Calculate the linear correlation and graph correlationmatrix.- Radar graph of each brands customer engagement interm of music genres.- Bar chart comparing overall engagement between the twomusic genre. Scrape and joinlyrical dataNode 251Node 252Lyrical simplicityNode 360Node 365Correlationbetween allvariables in branddataCorrelation matrixNode 415Node 416Node 422Node 423Node 424Node 428 Brand_data Prep Document Creator Preprocessing Compressibility Scatter Plot Line Plot Linear Correlation Heatmap Bar Chart Bar Chart Individual brandengagement by genres Optimizing K_Clusters(2:80) (1:10) (70:80) Optimal K = 2 Sentiment Analysis Joining data Data Optimization TOPIC EXTRACTION AND ANALYSIS OF ALL THESONGS USED BY CROCS, GYMSHARK ANDTARGETThe result of k-mean optimization indicate that the recommended number oftopics is 80, in which i believe is a case of over fitting, because it is 77topics out of 18 unique songs=> which led me to believe that brands use a wide range of song that fitstheir purpose.But, when boiled down to 2 topic, it might indicate that these are wordsmost commonly used in POP(Softcore) and HIP-HOP/RAP(Hardcore)This could be verified by some of the artist in the list, Post Malone,Kendrick Lamar, Juice WRLD VARIABLES RELATIONSHIPS- Calculate the linear correlation and graph correlationmatrix.- Radar graph of each brands customer engagement interm of music genres.- Bar chart comparing overall engagement between the twomusic genre. Scrape and joinlyrical dataNode 251Node 252Lyrical simplicityNode 360Node 365Correlationbetween allvariables in branddataCorrelation matrixNode 415Node 416Node 422Node 423Node 424Node 428 Brand_data Prep Document Creator Preprocessing Compressibility Scatter Plot Line Plot Linear Correlation Heatmap Bar Chart Bar Chart Individual brandengagement by genres Optimizing K_Clusters(2:80) (1:10) (70:80) Optimal K = 2 Sentiment Analysis Joining data Data Optimization

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Created by: Admin
Created at: 2021-11-29
On NodePit since: 2021-12-06
Last update: 2024-04-26
Created with KNIME version: v4.4.1

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