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Predicting IMDB Movie Ratings Using Social Media [chapter]

Andrei Oghina, Mathias Breuss, Manos Tsagkias, Maarten de Rijke
2012 Lecture Notes in Computer Science  
We predict IMDb movie ratings and consider two sets of features: surface and textual features.  ...  For the latter, we assume that no social media signal is isolated and use data from multiple channels that are linked to a particular movie, such as tweets from Twitter and comments from YouTube.  ...  Conclusions and Outlook We addressed the task of predicting movie ratings using data from social media.  ... 
doi:10.1007/978-3-642-28997-2_51 fatcat:rjlacxnfdnhwdkcezmxbsuuy4m

Prediction of Movie Performance using Machine Learning Algorithms

Shubham Pawar
2020 International Journal for Research in Applied Science and Engineering Technology  
In this proposed system, we give our detailed analysis of the Internet Movie Database (IMDb) and predict the IMDb score.  ...  The proposed system provides a quite efficient approach to predict IMDb score on IMDb Movie Dataset. We will try to unveil the important factors influencing the score of IMDb Movie Data.  ...  Therefore, it is very straightforward to predict IMDb movie ratings when it comes to predicting the liking of audiences.  ... 
doi:10.22214/ijraset.2020.2102 fatcat:i3uozilpy5g6rgxbnceidmbmjq

Movie Rating Prediction using Ensemble Learning Algorithms

Zahabiya Mhowwala, A. Razia, Sujala D.
2020 International Journal of Advanced Computer Science and Applications  
However, it has become a trend to predict the rating of the movie based on the data collected from social media related to the movie.  ...  In this report, the aim is to collect movie data from IMDB and its social media data from YouTube and Wikipedia and compare the performance of two machine learning algorithms -Random Forest and XGBoostbest  ...  The data used for the model [3] is from IMDb movie data and social media data from Twitter and Wikipedia. These features are then used in factorization machines to predict the ratings of the movie.  ... 
doi:10.14569/ijacsa.2020.0110849 fatcat:mu5esdy6v5ezlare6gkpp6g2na

Predicting Ratings for New Movie Releases from Twitter Content

Wernard Schmit, Sander Wubben
2015 Proceedings of the 6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis  
In this study, a corpus of tweets was compiled to predict the rating scores of newly released movies on IMDb.  ...  Similar to the public voting mechanism on websites such as the Internet Movie Database (IMDb) that aggregates movies ratings, Twitter content contains reflections of public opinion about movies.  ...  This includes regression experiments in order to predict the IMDB rating of the movie.  ... 
doi:10.18653/v1/w15-2917 dblp:conf/wassa/SchmitW15 fatcat:rdnoeeqsgnbglj65pj3kgjkbpu

Movie Success Prediction using Historical and Current Data Mining

Partha Chakraborty, Md. Zahidur, Saifur Rahman
2019 International Journal of Computer Applications  
Some of the factors in predicting movie success are budget, actors, director, producer, IMDb rating, IMDb metascore, IMDb vote count, rotten tomator's tomatometer, actors and director social fan following  ...  Be that as it may, success can not be predicted based on a specific property of a movie.  ...  The movie success prediction was based on social media success count, and historical data. The predictions can be made about new movies using this study.  ... 
doi:10.5120/ijca2019919415 fatcat:araryqltnzdqtdkgh2gba67ktm

Movie Rating Prediction using Convolutional Neural Network based on Historical Values

Rudy Aditya Abarja
2020 International Journal of Emerging Trends in Engineering Research  
Many existing researches failed to address this problem because they used the post-release elements such as social media comments to predict movie rating.  ...  By using historical values, objective prediction can be made even before the movie released. The proposed method was intended to make more accurate and general prediction for movie rating.  ...  IMDb dataset has several social media data such as actor, movie, director and total cast Facebook like count.  ... 
doi:10.30534/ijeter/2020/109852020 fatcat:2heq4clkgjabfkhvc22fc56cxe

Using Social Media to Predict Future Events with Agent-Based Markets

Efthimios Bothos, Dimitris Apostolou, Gregoris Mentzas
2010 IEEE Intelligent Systems  
The cutoff values we used were 2.5 for IMDb ratings and 25 for Flixster ratings.  ...  For ratings, IMDb uses a 1 to 5 scale, and Flixster a scale of 10 to 50.  ... 
doi:10.1109/mis.2010.152 fatcat:77v7gjlsnjgu3nb4nw2mcanjky


2021 Pazarlama ve pazarlama araştırmaları dergisi  
Engagement measures, namely view, likes, dislikes, and shares of the official movie trailer on YouTube, on the movie's official Facebook page, consumer and critic reviews on IMDB were recorded the release  ...  While engagement on YouTube was the most effective at the earlier stage of the movie screen, engagement on a Facebook page was the most effective at a later stage of the movie screen.  ...  at IMDB (user rating) Average user rating of a movie at IMDB (weekly) (10-point rating) User volume at IMDB (UserVolume) The volume of user engagement at IMDB.  ... 
doi:10.15659/ppad.14.3.932621 fatcat:wvd4j63ztbardk7edzxoigj7au

Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation
영화 추천 시스템의 초기 사용자 문제를 위한 장르 선호 기반의 클러스터링 기법

Tithrottanak You, Ahmad Nurzid Rosli, Inay Ha, Geun-Sik Jo
2013 Journal of Intelligence and Information Systems  
Introduction Social media has become one of the most popular media in web and mobile application.  ...  Moreover, we use the Internet Movie Database (IMDb 10) ) as the main dataset.  ... 
doi:10.13088/jiis.2013.19.1.057 fatcat:3ee6utxq5bhwhauihfezqdrjre

Predicting Product Performance with Social Media

Liviu LICA, Mihaela TUTA
2011 Informatică economică  
how social media can be used for predicting the success of a product or service.  ...  To showcase this, two case studies are presented; a test to prove that the conversations that take place in social media are a good indicator of success and the second is an exercise to predict the winner  ...  Acknowledgement This work was co financed from the European Social Fund through Sectoral Operational Programme Human Resources Development 2007-2013, project number POS-DRU/107/1.5/S/77213 "Ph.D. for a  ... 
doaj:9de4a33032c949cca60daa0fc27c6443 fatcat:vg3gjwvnvffolersoianwe27ci

Social Network Analysis of the Professional Community Interaction – Movie Industry Case [article]

Ilia Karpov, Roman Marakulin
2021 arXiv   pre-print
Based on publicly available data we create an "actor"-"casting director"-"talent agent"-"director" communication graph and show that usage of additional knowledge leads to better movie rating prediction  ...  This paper focuses on new approaches to predict film success, based on the movie industry community structure, and highlights the role of the casting director in movie success.  ...  Another attempt to predict IMDb scores was taken by Rudy Aditya Abarja and Antoni Wibowo in their article "Movie Rating Prediction using Convolutional Neural Network based on Historical Values" [5] .  ... 
arXiv:2109.01722v1 fatcat:qbmxmbhspjah7cadfxq4k4gy5y

Using Online User-Generated Reviews to Predict Offline Box-Office Sales and Online DVD Store Sales in the O2O Era

Chieh Lee, Xu Xun, Lin Chia-Chun
2019 Journal of Theoretical and Applied Electronic Commerce Research  
Via predictive global sensitivity analysis, this study uses online user-generated reviews posted on social media to predict customers' demand for hyper-differentiated products both online and offline,  ...  With the rapid growth of e-commerce and social media, customers post online reviews on various online shopping websites and social media after their consumption experience, which generated the electronic  ...  on social media before and after the release of the movie [27] .  ... 
doi:10.4067/s0718-18762019000100106 fatcat:3qy6n4emh5hutdbjosrwcgrhky

Flick Fortune: Movie Gross Prediction using Data Analysis and Prediction

V. Balamurugan
2018 International Journal for Research in Applied Science and Engineering Technology  
We coherently apply the proposed system onto the movie prediction such as Gross collection, Rating, feedback and success ratio.  ...  We use web scrapper code with TMDB API to fetch attributes of the movies such as actor name, director, musician, producer and budget.  ...  The movie success prediction was based on social media success count, and historical data. The predictions can be made about new movies using this study.  ... 
doi:10.22214/ijraset.2018.4799 fatcat:ucdtdbgodbd6hcr6a4v4lb7b7u

A Hybrid Recommendation System of Upcoming Movies Using Sentiment Analysis of YouTube Trailer Reviews

Sandipan Sahu, Raghvendra Kumar, Pathan MohdShafi, Jana Shafi, SeongKi Kim, Muhammad Fazal Ijaz
2022 Mathematics  
This method fuses the predicted rating and preferred list of upcoming movies from modules one and two. This study used publicly available data from The Movie Database (TMDb).  ...  Our experimental results established that the predicted rating of unreleased movies had the lowest error.  ...  Social media data can be used to understand user's characteristics. Dang et al.  ... 
doi:10.3390/math10091568 fatcat:vnhq7mdcbjd5dh3hcnfhfk6jly

Business Intelligence from Social Media: A Study from the VAST Box Office Challenge

Yafeng Lu, Feng Wang, Ross Maciejewski
2014 IEEE Computer Graphics and Applications  
These visual analysis method used in our system can be generalized to other domain where social media data is involved, such as sales forecasting, advertisement analysis, etc.  ...  This paper presents a visual analytics system which extracts data from Bitly and Twitter to use for box office revenue and user rating predictions.  ...  Monsters Universitys IMDB rating was 7.8 giving us confidence that our predicted value of 7.8 was reasonable.  ... 
doi:10.1109/mcg.2014.61 pmid:25248200 fatcat:xojqbdrqfzbodlrh3y43h6ohce
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