Challenge

The mobile games sector seems to be one of the fast growing industries due to the rising of  mobile market. With the advancement of mobile technology, mobile devices can now be used  as a mobile media centre. One of the emerging areas is also in using it for gaming. Because of  Google Play store, today numerous different games are offered to every Smartphone user. This  diversity in supply is a good thing, but it also disables users to find games they would like to  play. I wanted to make a personalized mobile game recommendation system which takes into  consideration various factors those are responsible for game selection and installation.

There were two main goals of this experiment:

⦁  To study the effect of various factors those are responsible for game selection and  installation.

⦁  To propose a better recommendation system that incorporates all the factors in making  recommendation and compares the performance of our proposed approach with that  of the classical one.

Selection

We decided to use mind mapping and brainstroming in order to collect all the major factors  responsible for game selection and categorize them according to group which they found  similarity with. Mind mapping steps includdes picking out the good stuff from the invidiuals  notes and his new ideas. cluster the good ideas and identify the insights related to each cluster  and look for connections between clusters.

Application

Factors responsible for game selection are found out from:

⦁  Research papers using keywords (mobile games/ computer games).

⦁  Game players (All the top game players and game developers).

7 Research papers were read to find out all the important factors that lead to game selection  and installation.

24 undergraduate were invited and participated in this research.

Major points in Game design found out through research papers.

Computer Games:Exploration, and educational.( Amory, A., Naicker, K., Vincent., & Adams, C.  (1999)), Challenge, Fantasy, curiosity. (Malone, T. W. (1980)), Positive Reinforcement, increase  social. (Squire, K. (2002)), 4.Self-Determination, competence, psychological satisfaction, Game

variable, Intuitive controls, Presence, Motivation, Enjoyment, Preference for future play,  Change in well-being, Vitality, Self-esteem, Mood/effect. (Ryan, R.M., Rigby, C.S. & Przybylski   (2006)), Fun, play, rules, goals, interactive, adaptive, outcomes, feedback, ego gratification,  competition, problem-solving, interaction, and emotion. (Prensky, M. (2001))

Mobile Games: Game should be challenging, personal liking and vision, social contents,  communication -social playability,Motivational, inspirational

Internet Games: Reasons People Play Online Games, Passing Time, Entertainment, Challenge  Competition, Fantasy and Roll Playing , Self-Presentation, Social Interaction, Triggered  Emotions, Energetic, Engagement, Joy, Happiness, Love, Enthusiasm, Anxiety, Fear, Hate,  Worry, Distress, Anger, Hostility, Disgust

Major Factors responsible find out through brain storming session: Action, puzzle, games,  multiplayer, Game-ram, graphics, Mood, free time, recreation, Unique idea, Requirements and  compatibility, Simple controls, Education, Social like pub-g, Easy and interesting stages,  Storyline, Reviews, Description, new idea, Same interest like sports, More stages and big game,  More manual then automatic,Movie based. (good story).

Major Factors responsible for android games selection find out through personal interaction:  Download size, social interaction, Gameplay and prize, Graphics, Friend circle and lists, Maps  and gameplay, Offline availability, Insta-ads and recommendation from friends etc, Better  understanding the game/ judge through icons, Mood effect.(recreation/bore), Interest of  games.

Factors responsible for video games selection find out through personal interaction:  Competition.(multiplayer(fps)),Storyline (single player games), YouTube/ insta ads/reviews,  Trailer/game play, Brand of games, Skill/interaction/tools, Mood effect, Graphics/content/game  play, Prizes, Values/aesthetics, Maps/rules/fun, Fare games matches.

Our preliminary analysis is based on the factors that are found out using by the 5 subjects who  were approached to find out all the factors responsible. Then, a brain storming session was  done with the 5 subjects to find all the factors other than the factors found out in research  papers.

Insight

By applying mind mapping, we divided all the factors into three major groups: Game specific,  Device specific, Socio-psychological factors.

Game specific: All the factors that Depends on the Game we are taking into consideration were  added into Game specific Group.

Device specific: All the factors that Depends on the specification of device we are using to play  the Game were added into Device specific Group.

Socio-psychological factors: All the factors that are related to social and psychological state of

the user playing the game were added into Socio-psychological factors group.

Approach

Further to find pattern in this huge amount of data we used similarity scores. after taking rating  from game users,Some users considered as subject for recommendation, Compared rating of  users with other users and computed similarity scores,Used similarity scores to make prediction  for each game which is not played, Recommended game with highest prediction value.

Organization

IIT Roorkee

Additional Feedback

This research will also help game developers and game companies to make better games for the

game players according to their need.


Challenge The mobile games sector seems to be one of the fast growing industries due to the rising of mobile market . With the advancement of mobile technology , mobile devices can now be used as a mobile media centre . One of the emerging areas is also in using it for gaming . Because of Google Play store , today numerous different games are offered to every Smartphone user . This diversity in supply is a good thing , but it also disables users to find games they would like to play . I wanted to make a personalized mobile game recommendation system which takes into consideration various factors those are responsible for game selection and installation . There were two main goals of this experiment : ⦁ To study the effect of various factors those are responsible for game selection and installation . ⦁ To propose a better recommendation system that incorporates all the factors in making recommendation and compares the performance of our proposed approach with that of the classical one . Selection We decided to use mind mapping and brainstroming in order to collect all the major factors responsible for game selection and categorize them according to group which they found similarity with . Mind mapping steps includdes picking out the good stuff from the invidiuals notes and his new ideas . cluster the good ideas and identify the insights related to each cluster and look for connections between clusters . Application Factors responsible for game selection are found out from : ⦁ Research papers using keywords ( mobile games/ computer games ) . ⦁ Game players ( All the top game players and game developers ) . 7 Research papers were read to find out all the important factors that lead to game selection and installation . 24 undergraduate were invited and participated in this research . Major points in Game design found out through research papers . Computer Games : Exploration , and educational . ( Amory , A. , Naicker , K. , Vincent . , & Adams , C. ( 1999 ) ) , Challenge , Fantasy , curiosity . ( Malone , T. W. ( 1980 ) ) , Positive Reinforcement , increase social . ( Squire , K. ( 2002 ) ) , 4.Self - Determination , competence , psychological satisfaction , Game variable , Intuitive controls , Presence , Motivation , Enjoyment , Preference for future play , Change in well - being , Vitality , Self - esteem , Mood / effect . ( Ryan , R.M. , Rigby , C.S. & Przybylski ( 2006 ) ) , Fun , play , rules , goals , interactive , adaptive , outcomes , feedback , ego gratification , competition , problem - solving , interaction , and emotion . ( Prensky , M. ( 2001 ) ) Mobile Games : Game should be challenging , personal liking and vision , social contents , communication -social playability , Motivational , inspirational Internet Games : Reasons People Play Online Games , Passing Time , Entertainment , Challenge Competition , Fantasy and Roll Playing , Self - Presentation , Social Interaction , Triggered Emotions , Energetic , Engagement , Joy , Happiness , Love , Enthusiasm , Anxiety , Fear , Hate , Worry , Distress , Anger , Hostility , Disgust Major Factors responsible find out through brain storming session : Action , puzzle , games , multiplayer , Game - ram , graphics , Mood , free time , recreation , Unique idea , Requirements and compatibility , Simple controls , Education , Social like pub - g , Easy and interesting stages , Storyline , Reviews , Description , new idea , Same interest like sports , More stages and big game , More manual then automatic , Movie based . ( good story ) . Major Factors responsible for android games selection find out through personal interaction : Download size , social interaction , Gameplay and prize , Graphics , Friend circle and lists , Maps and gameplay , Offline availability , Insta - ads and recommendation from friends etc , Better understanding the game/ judge through icons , Mood effect.(recreation / bore ) , Interest of games . Factors responsible for video games selection find out through personal interaction : Competition.(multiplayer(fps)),Storyline ( single player games ) , YouTube/ insta ads / reviews , Trailer / game play , Brand of games , Skill / interaction / tools , Mood effect , Graphics / content / game play , Prizes , Values / aesthetics , Maps / rules / fun , Fare games matches . Our preliminary analysis is based on the factors that are found out using by the 5 subjects who were approached to find out all the factors responsible . Then , a brain storming session was done with the 5 subjects to find all the factors other than the factors found out in research papers . Insight By applying mind mapping , we divided all the factors into three major groups : Game specific , Device specific , Socio - psychological factors . Game specific : All the factors that Depends on the Game we are taking into consideration were added into Game specific Group . Device specific : All the factors that Depends on the specification of device we are using to play the Game were added into Device specific Group . Socio - psychological factors : All the factors that are related to social and psychological state of the user playing the game were added into Socio - psychological factors group . Approach Further to find pattern in this huge amount of data we used similarity scores . after taking rating from game users , Some users considered as subject for recommendation , Compared rating of users with other users and computed similarity scores , Used similarity scores to make prediction for each game which is not played , Recommended game with highest prediction value . Organization IIT Roorkee Additional Feedback This research will also help game developers and game companies to make better games for the game players according to their need .