Presentor :Gigi Tang Instructor: Terasa Hsu Date: May 11, 2015

Predicting Movie Prices Predicting Movie Prices Through Dynamic Social Through Dynamic Social Network AnalysisNetwork Analysis

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Contents

Introduction

Method

Modeling

Conclusion

Reflection

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Citation

Doshi, L., Gloor, P., Krauss, J., & Nann. S. (2010). Predicting Movie Prices Through Dynamic Social Network Analysis. Procedia Social and Behavioral Science 2, 6423-6433.

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Definition of terms

HSX: Hollywood Stock Exchange

IMDb: Internet Movie Database

SNA: Social Network Analysis

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Introduction

Purpose of this research:

Predict prices and trade on the Hollywood Stock Exchange (HSX)

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Three of metrics

Group I: IMDb and Rotten Tomatoes

Group II: SNA Metrics Web and blog

Group III: Sentiment about movies base on

forums

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Method1.Data Sources

2.User Ratings

3.Social Network Analysis (SNA) Metrics

4.Sentiment Analysis Metrics

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Purpose

1.Predict the daily changes in prices

2.Predict the final closing price of the stock

after four weeks

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Data Sources

Web Metrics

Social Network Analysis Metrics

Sentiment Metrics

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User Ratings

IMDb

Rotten Tomatoes

Box Office Mojo

Hollywood Stock Exchange

Snowball Effects 10

SNAForumBlogosphere

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Sentiment Analysis Metrics

1.Basic Sentiment Algorithm

2. Dynamic Adaptation of Bag-of-Words

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Sentiment Analysis MetricsOscar Buzz Film General

Upcoming Films Box Office

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Basic Sentiment Algorithm

Shown that automatic extraction of words and word pairs leads to more precise result than manually selecting positive and negative words.

(Pang & Lee,2002)

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Dynamic Adaptation of Bag-of-Words

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Modeling

1.Liner Regression

2.Classifying Movies as Successes or Flops

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Linear Regression

This table are related, but not directly linked

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Classifying Movies as Successes or Flops

Group III: Sentiment about movies based on the forums did well in categorized

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Classifying Movies as Successes or Flops

Group II: SNA Metrics Web and blog classified against false positives

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Classifying Movies as Successes or Flops

Group I: IMDb and Rotten Tomatoes Group III: Sentiment about movies base on forums

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Group II: SNA Metrics Web and blog

Conclusion

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Reflection

I hope the predicting in the movie not only how well we think the movie will perform, but also how we think other people think the movie will perform.

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