Profiling Smurfs And Boosters on Dota 2 Using K-Means
Dota 2 is one of the most popular Multiplayer Online Battle Arena (MOBA) game and it also holds the grandest e-Sports tournament in the world —— The International. However, the game is experiencing a continuous decline in its player count. This is because the existence of smurfs/boosters in Dota 2 i...
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| Format: | Final Year Project / Dissertation / Thesis |
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2021
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| Online Access: | http://eprints.utar.edu.my/4091/ http://eprints.utar.edu.my/4091/1/1904956_FYP_report_%2D_YING_JIH_DING.pdf |
| _version_ | 1848886073858457600 |
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| author | Ding, Ying Jih |
| author_facet | Ding, Ying Jih |
| author_sort | Ding, Ying Jih |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | Dota 2 is one of the most popular Multiplayer Online Battle Arena (MOBA) game and it also holds the grandest e-Sports tournament in the world —— The International. However, the game is experiencing a continuous decline in its player count. This is because the existence of smurfs/boosters in Dota 2 is ruining the game experience for all other Dota 2 players. Hence, this project aims to identify the smurfs/boosters and analyse their skills. The data were collected from OpenDota API and a data set was created after cleaning and pre-processing. To identify the smurfs and boosters in the data set, K-Means was used to divide the players into groups. To identify the high-skill players group, feature values of the data were examined. Interquartile Range (IQR) method was then used on the high skill players group to identify and profile smurfs/boosters. The resulted profile was reviewed by two game experts and one active player. A 95% accuracy score was achieved using majority voting. It is hoped that this work can be furthered for identifying the different skill levels of the smurfs/boosters after identifying them. |
| first_indexed | 2025-11-15T19:32:42Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-4091 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:32:42Z |
| publishDate | 2021 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-40912021-06-11T19:22:58Z Profiling Smurfs And Boosters on Dota 2 Using K-Means Ding, Ying Jih QA76 Computer software Dota 2 is one of the most popular Multiplayer Online Battle Arena (MOBA) game and it also holds the grandest e-Sports tournament in the world —— The International. However, the game is experiencing a continuous decline in its player count. This is because the existence of smurfs/boosters in Dota 2 is ruining the game experience for all other Dota 2 players. Hence, this project aims to identify the smurfs/boosters and analyse their skills. The data were collected from OpenDota API and a data set was created after cleaning and pre-processing. To identify the smurfs and boosters in the data set, K-Means was used to divide the players into groups. To identify the high-skill players group, feature values of the data were examined. Interquartile Range (IQR) method was then used on the high skill players group to identify and profile smurfs/boosters. The resulted profile was reviewed by two game experts and one active player. A 95% accuracy score was achieved using majority voting. It is hoped that this work can be furthered for identifying the different skill levels of the smurfs/boosters after identifying them. 2021 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4091/1/1904956_FYP_report_%2D_YING_JIH_DING.pdf Ding, Ying Jih (2021) Profiling Smurfs And Boosters on Dota 2 Using K-Means. Final Year Project, UTAR. http://eprints.utar.edu.my/4091/ |
| spellingShingle | QA76 Computer software Ding, Ying Jih Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title | Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title_full | Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title_fullStr | Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title_full_unstemmed | Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title_short | Profiling Smurfs And Boosters on Dota 2 Using K-Means |
| title_sort | profiling smurfs and boosters on dota 2 using k-means |
| topic | QA76 Computer software |
| url | http://eprints.utar.edu.my/4091/ http://eprints.utar.edu.my/4091/1/1904956_FYP_report_%2D_YING_JIH_DING.pdf |