Data Analysis Research on Music
52 Pages13993 Words124 Views
Added on 2020-04-21
Data Analysis Research on Music
Added on 2020-04-21
ShareRelated Documents
DATA ANALYSIS Name:Student ID:Supervised by: Date:
AbstractMusic has significant role in all the events in the world. The current research revolves around theArgentine Tango dance party or events and the DJs’ from all the corners of the world. The mainobjective of this research is to measure the factors which holds key role in selection of musictrack’s list for worldwide DJs, to play in the Tango events, and to certify these music tracks withhigh influence, from the Data Analysis scope. Thus, this research aims to answer- “What candata analysis reveal from the selection of music tracks by DJs in Tango music events and how?”which helps in enhancing the event. This research supports to answer the factors which influencethe track selection and in which degree. Data analysis tool is used for clarifying the patterns. TF-IDF (term frequency–inverse document frequency), data mining and data visualisation methodsare used in this research. SPSS software is used for data analysis of the current research. Thecurrent research has another set of objectives i.e., to observe the correlation between theprovided music data and then to qualify the type of music played for entertaining the crowd invarious geographical regions, and for different events. The overall goal of the research method isto answer the following questions- How does the preferences change over time? Find the regionwhich will probably begin with a new trend? Determine the duration for the average lifecycle ofa hit i.e., from peak to decay? Identify the highly played orchestras in all the continents? Howwill the dance tempo impact the event from beginning to end? Recognize the most often orhighly played music tracks in all the continents and how are these tracks compared? Does thereexists any pattern for music track selection based on the event type or day? Mention theresemblance or differences of track selection, from different DJs of different parts of the world?Initially, the research gathers the track playlists from different DJs present in various parts of theworld. Next step includes data processing with the help of data analysis i.e., data mining throughvisualization. Visualization is this research’s product. This research provides music datavisualization. The beneficiaries of this research are determined. The respective results arerepresented and discussed briefly. The limitations of the current research are highlighted.Further, the reflections of the research, its methods and procedures are reflected in the later partof the research. The achievement and future work of the research are also presented.
Table of Contents1.Introduction............................................................................................................................11.1Background......................................................................................................................11.1.1Why this research?..................................................................................................31.1.2Information Visualization.......................................................................................41.2Research Questions.........................................................................................................41.3Why did I choose the Project.........................................................................................41.4Beneficiaries.....................................................................................................................51.5Products of this Research...............................................................................................51.6Research Objectives........................................................................................................51.7Scope and Definition.......................................................................................................61.8Methods............................................................................................................................71.8.1Software Development Methodology.....................................................................71.9Testing the Objectives.....................................................................................................81.10Structure of Dissertation................................................................................................82.Critical Context......................................................................................................................92.1Approach..........................................................................................................................92.2Visual Analytics.............................................................................................................10Process of Visual Data Analytics............................................................................................11Building blocks of Visual Analytics........................................................................................112.3Visual Data Mining.......................................................................................................123.Method...................................................................................................................................133.1Participants....................................................................................................................133.2Materials........................................................................................................................143.3Methods..........................................................................................................................14
3.4Procedures.....................................................................................................................144.Results....................................................................................................................................185. Discussion.................................................................................................................................381.1Validity of Results.........................................................................................................411.2Generalization of Results..............................................................................................422.Evaluation, Reflections and Conclusion.............................................................................432.1Literature Review.........................................................................................................432.2Reflection on Topic and Objectives.............................................................................432.3Reflection on the Selected Methods.............................................................................442.4Reflection on the Plan...................................................................................................442.5Accomplishment............................................................................................................452.6Conclusion......................................................................................................................462.7Future work...................................................................................................................47References.....................................................................................................................................47
1.IntroductionThis project is the result of data collection and visualization, which aims to delivertrusted and quality information. All the people in the world attract to good music, and theinvolvement of audience in the events can change the reputation of the conducted event. Thecurrent research project concentrates on generating music data visualization, for helping the DJsin the music track’s selection process, by analyzing the effectiveness of the selected music trackplaylist for the Tango music events. This research includes convincing the DJs to contribute help in the selection of musictracks, for the Tango music events. Next, it requires gathering of data, data mining and reportingthe results. Once the visualization is provided successfully, it could contribute to enhancing thetango music event. This research aims to measure the factors which plays a prominent role toselect the music track-list, and to certify these music tracks such that it increases its influence. Italso foresees to observe the correlation between the supplied music data and to qualify the typeof music played for meeting the crowd’s needs. Thus, the music industry uses data miningmethod for enhancing the experiences of their audience. This research opts SPSS software forcompleting the data analysis. 1.1BackgroundThis section highlights the basic knowledge of the current research, which assists infollowing the conducted research. Music is a vital part of all the events, worldwide. This researchrevolves around the Argentine Tango dance party, also known as “Milonga”. The DJs have amajor role in this party, as they play four selected tango music tracks. But, at times, they justplay three tango tracks. A set of songs is referred as “Tanda”. The DJs play short snippets ofnon-tango songs, amid tandas which are known as “Cortinas”. In general, the Tango festivals areannual events, which are conducted for many days around the weekend. Popular dancers andinstructors are part of this event. In general, the tandas consists of various rules and regulations,which completely depends on the DJs. The DJs has all the rights to play the tango playlist as pertheir wish. Therefore, here data mining is required to scrutinize the playlist, which is collectedfrom various DJs of worldwide. The collected music data is decreased for declining the risk ofthreat. The collected music track playlist will contain specific information, to ensure data miningwith the help of visualization could generate optimal results. For the data analysis, orchestra and1
the track name has significant importance. Every single playlist should contain its location, time,season and the event type they were played for. This type of details will help in retrievingaccurate results. Furthermore, the information like, audience type and DJ’s background acts ascomplementary information which helps in reducing the risks of errors in the results. Varioustango events can have positive or negative impact due to the DJ’s music selection. It is stated thatthe local milongas could be held periodically or regularly or it can be conducted as a specialevent. The Tango festivals comprises a mix of instructional classes and workshops, it alsoincludes the instructors’ performances and milongas, which grasps the attention of the dancerswho come from all the parts of the world. These dancers are well experienced. In such socialevents, the DJs are referred as key entertainer, and makes the crowd enjoy their played musictracks. The Tango marathons has similar schedule like the other type of events, where the onlyexception is that they omit classes or workshops and it mainly attracts seasoned dancing. TheDJs regulate the event with their selected music track, which maintains crowd’s good mood andthey consider it as their responsibility to keep the whole event enjoyable. This observedrequirements of this research is to perform data mining, to take right decision by right insight forcompleting the research process. To help this research, SPSS software is utilized foraccomplishing data analysis. Some of the playlists that are utilized are as follows: 1)Budapest marathon is dancer level 3 (1-5) in Budapest. 2)Avrig can be listed as casual festival with dancer level 3, in Romania.3)Cuib is a local Milonga, dance level 2 in Romania 4)Sibiu is festival, dancer level 3, in Romania 5)Anivertango is marathon, dancer level 4, Romania The DJ belongs from Romania, who is a female aged 30 years.The locations selected for this research are listed below: 1)London2)Miami US3)Providence US2
4)Brussels 5)Florida Keys USThe provided even type is mentioned in the below section:a)Local Milongab)Local practicac)Evening millongad)Outdoors versus. not outdoors Experience dancers (Five) and unexperienced dancers (one) are considered, as follows: Providence US: 2 Miami US: 3 Florida Keys: 4 Brussels: 3 London: 3The expectations of this research includes- The DJs requires generating a track playlistwith factors that influence the Tango events, to select right music track. The playlist must dependon the stereotype, for various factors and must correspond with the analysis’s inputs. The factorscould be the even type, geographic location of the event and crowd. It is also noticed that it canbe checked for the experience of the event and how it varies over time.1.1.1Why this research?This research is used for providing a famous data mining method for identifying thesimilarities, patterns and correlation. The earlier tools failed to provide effective results. But, thecurrently utilized data mining method for visualization is, comparatively instant and moreeffective. In case of accomplishing this research, it furnishes visualization for enhancing thecapacity to explore the data. Thus, this research will then generate appropriate music playlist’sstereotypes, which is based on multiple factors and corresponds with the factors like event type,audience and geographic location, type of event, audience and its variation with time. However,this outcome influences the Tango event’s DJs. On the other hand, it helps the music industry,3
which enhances experiences of the audience and in turn increases their profit. For added profit, itis required that the music track must match the seasonal trend and place. And this requirescorrelation, which can be found by data mining process. Further, it handles large data collectionand also identifies various patterns from it. 1.1.2Information VisualizationInformation Visualization is also known as InfoVis. It represents a type of study that hasvisual representations of abstract data which could be numerical and non-numerical. Forinstance, text or geographic information. Thus, this type of data helps to have interactivity, it alsoprovides clear understanding and it can identify the difficult data patterns. InfoVis is an onlinesource which is reachable to large number of research audience (Sindiy et al., 2013). Iteffectively and instantly identifies the anomalies along with the data patterns. It is a toolespecially used for large dataset (Robertson and Kaptein, 2016).1.2Research QuestionsThe important question of this research is to resolve: “What can data analysis reveal fromthe selection of music tracks by DJs in Tango music events and how?” Hence, this question’sanswer determines whether, the data analysis of the provided playlists being played in Tangoevents- from DJs around the world, could help in enhancing it, then in tango event which factorscould influence the track selection and in which degree. The patterns are clarified based on dataanalysis tool. 1.3Why did I choose the ProjectFor visualization, music data is an interesting platform. My personal opinion onvisualization can help to improvise the data for conveying and to present to the analysts foreasing their work. On the other hand, it has the flexibility to visually recognize and manipulatethe data, by addition and removal of new insights on the data. Tango events are very popular andit includes contribution of various DJs from different parts of the world, for gathering the musictrack playlist/ data. In contains various events and with different crowd. Satisfaction of thecrowd, by entertaining them is the ultimate goal of this event. If the crowd is not satisfied then it4
End of preview
Want to access all the pages? Upload your documents or become a member.
Related Documents
Business Analytics and Data Mining Techniques for Banking Industrylg...
|11
|1013
|76
Business Analytics and Data Mining Techniques for Banking Industrylg...
|7
|1200
|97
Market Research: Methods, Techniques, and Importancelg...
|8
|2147
|215
Mobile App of Wildlife of Qatarlg...
|15
|3495
|187
Credit Card Fraud Identification: A Complete Reviewlg...
|43
|7531
|457
Research Proposal Outline for Nursing Studentslg...
|4
|703
|184