UC San Diego UC San Diego Electronic Theses and Dissertations Title Essays on Political Economy of the Media Permalink https://escholarship.org/uc/item/76c987rx Author Lam, Onyi Publication Date 2017 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Essays on Political Economy of the Media A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Economics by Onyi Lam Committee in charge: Professor Roger Gordon, Chair Professor Gordon Dahl Professor James Rauch Professor Molly Roberts Professor Kenneth Wilbur 2017 Copyright Onyi Lam, 2017 All rights reserved. The dissertation of Onyi Lam is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2017 iii DEDICATION To my parents, Heung Wah Lam and Sau Man Ho, and my city, Hong Kong iv TABLE OF CONTENTS Signature Page ....................................... iii Dedication ......................................... iv Table of Contents ..................................... v List of Figures ....................................... viii List of Tables ........................................ xi Acknowledgements ..................................... xiii Vita ............................................. xiv Abstract of Dissertation .................................. xv Chapter 1 Advertisers Capture: Evidence from Hong Kong ............. 1 1.1 Introduction .................................... 1 1.2 Suggestive Evidence ............................... 5 1.3 Institutional Context ............................... 6 1.3.1 Business and Politics ........................... 7 1.3.2 Participation in Mainland Politics ................... 8 1.3.3 Newspaper Market ............................ 8 1.4 Illustrative Model ................................. 9 1.5 Data ........................................ 15 1.5.1 Advertising ................................ 15 1.5.2 Politically Connected Advertisers .................... 16 1.5.3 Readers’ Demography .......................... 18 1.6 Measuring Slant Gap .............................. 19 1.6.1 Selecting Phrases ............................. 20 v 1.6.2 Mapping Phrases to Slant ........................ 21 1.7 Empirical Evidence ................................ 23 1.7.1 Persistence of Slant Gap’s Effect .................... 28 1.7.2 Real Estate Industry ........................... 29 1.7.3 Alternative Measure of Political Climate . 31 1.8 Mechanisms .................................... 32 1.9 Apple Daily’s Revenue Loss ........................... 33 1.10 Conclusions .................................... 35 1.11 Figures and Tables ................................ 40 1.12 Appendix ..................................... 60 1.12.1 Sample of Apple Daily and Oriental Daily Headline during Occupy Central .................................. 60 1.12.2 Endogenous Readers’ Choice of Newspaper . 61 1.12.3 Finer Time Unit for Slant Gap ..................... 64 1.12.4 Polarization of the Benchmark Language . 65 1.12.5 Time Series of the Number of Pro-Democracy Phrases . 68 1.12.6 Political Ads and Government Ads ................... 69 Chapter 2 Measuring Subjectivity in History Textbooks . 70 2.1 Introduction .................................... 70 2.2 History Textbooks in Mainland China, Hong Kong and Taiwan . 74 2.3 Descriptive Statistics ............................... 76 2.3.1 Major Historical Episodes ........................ 77 2.4 Subjectivity Analysis ............................... 78 2.4.1 Adjectives and Adverbs ......................... 79 2.4.2 Political Entities ............................. 80 2.4.3 Text Polarity ............................... 81 2.4.4 Word Embedding ............................. 82 2.5 Prior and After Textbooks Reform ....................... 84 2.6 Writing Style ................................... 86 2.7 Conclusion .................................... 87 vi 2.8 Figures and Tables ................................ 92 Chapter 3 Celebrities Capture: Evidence from Weibo in China . 106 3.1 Introduction .................................... 106 3.2 Media Market in Mainland China . 109 3.3 Model ....................................... 110 3.4 Data ........................................ 114 3.4.1 Summary Statistics ............................ 115 3.5 Empirical Analysis ................................ 117 3.5.1 Athletes .................................. 119 3.5.2 Followers’ Reactions . 120 3.5.3 Facebook Accounts ............................ 121 3.5.4 Banned Entertainers . 122 3.6 Conclusion .................................... 122 vii LIST OF FIGURES Figure 1.1 Ad Share on print version of Apple Daily and Sing Tao relative to Sum of Apple, Oriental and Sing Tao. ..................... 40 Figure 1.2 Ad Share on print version of Apple Daily and Sing Tao relative to Oriental Only. ................................... 41 Figure 1.3 2016 Press Freedom Index issued by the Freedom House . 42 Figure 1.4 Hang Seng Index and relative Stock Price of the corporations that own Apple Daily (Next Digital, Ticker: 0282) and Oriental Daily (Oriental Press, Ticker: 0018) ............................... 44 Figure 1.5 Total number of ads assignments and ads assignments placed by con- nected organizations in each industry. ..................... 45 Figure 1.6 Ads Assignment by company characteristics . 45 Figure 1.7 Percentage of Connected Ad Assignment . 46 Figure 1.8 Percentage of Mainland Ad Assignment . 46 Figure 1.9 Difference in slant between the two newspapers. 48 Figure 1.10 Industry Fixed Effects Relative to the Real Estate Industry . 55 Figure 1.11 Industry Fixed Effects Relative to the Real Estate Industry . 55 Figure 1.12 Interaction terms between Industry and Slant Gap relative to the Real Estate Industry ................................. 56 Figure 1.13 Interaction terms between Industry and Slant Gap relative to the Real Estate Industry ................................. 56 Figure 1.14 Interaction terms between industry fixed effects and firms’ connectiv- ity for ads appearing on Apple only ...................... 57 Figure 1.15 Interaction terms between industry fixed effects and firms’ connectiv- ity for ads appearing on both newspapers ................... 58 Figure 1.16 Headline of Apple Daily on December 12, 2014. Translated as ”Do not forget the original intention. We will be back” . 60 viii Figure 1.17 Headline of Oriental Daily on December 12, 2014. Translated as ”Financier Jimmy Lai Pan-Democratic politicians accept bribes. Occupy Central Schemers All Caught” .......................... 60 Figure 1.18 Slant Gap Using Monthly Data .................... 64 Figure 1.19 A measure of polarization of word choices used by the benchmark . 66 Figure 2.1 Screenshot of the dictionary application on Mac showing the word Important ..................................... 92 Figure 2.2 Screenshot of the dictionary application on Mac showing the word Very 92 Figure 2.3 Pro-CCP to pro-KMT entities ...................... 96 Figure 2.4 Adjective Ratio .............................. 96 Figure 2.5 Adverb Ratio ............................... 97 Figure 2.6 Adjective Ratio of pre-1949 events ................... 97 Figure 2.7 Adjective Ratio of post-1949 events ................... 98 Figure 2.8 Adjective Ratio pre- and post- 1949 . 98 Figure 2.9 Adjective Ratio pre- and post- 1949 . 99 Figure 2.10 Positive to Negative Phrase Ratio pre- and post- 1949 . 99 Figure 2.11 Positive to Negative Phrase Ratio pre- and post- 1949 . 100 Figure 2.12 Positive to Negative Phrase Ratio in 4 major pre-1949 Historical Episodes ...................................... 100 Figure 2.13 Positive to Negative Phrase Ratio pre- and post- 1949 . 101 Figure 2.14 Adjective Ratio in Old and New Versions . 101 Figure 2.15 Adjective Ratio in Old and New Versions in pre- and post-1949 . 102 Figure 2.16 Adjective Ratio in Old and New Versions in pre- and post-1949 . 102 Figure 2.17 Positive to Negative Phrase Ratio pre- and post- 1949 . 103 Figure 2.18 Positive to Negative Phrase Ratio pre- and post- 1949 . 103 Figure 2.19 word embedding visualization of Mainland Chinese textbooks by t-SNE104 Figure 2.20 word embedding visualization of Hong Kong textbooks by t-SNE . 104 Figure 2.21 word embedding visualization of Taiwanese textbooks by t-SNE . 105 Figure 3.1 A popular post after the international tribunal in The Hague delivered its judgment ................................... 128 ix Figure 3.2 Number of Celebrities by Followers Group . 129 Figure 3.3 Number of celebrities Mentioned in Sina by Type . 129 Figure 3.4 Number of Celebrities (Performers only) Mentioned in Sina by Region 130 Figure 3.5 Number of celebrities Using Patriotic Phrases . 131 Figure 3.6 Number of celebrities Posting by Date Around 2016 July 13th . 132 Figure 3.7 Number of celebrities Posting by Date Around 2016 October 1st . 133 Figure 3.8 Number of times the celebrity is mentioned on Sina . 133 x LIST OF TABLES Table 1.1 Readership (’000) in 2014 (Including online readership) . 43 Table 1.2 Apple Daily’s Revenue Composition ................... 44 Table 1.3 Ad Price and Readership ........................ 47 Table 1.4 Readers Demography. The number indicates the fraction of readers reading the respective newspaper, except average Age, household income and totals. Source: AC Nielsen 2014. ........................ 47 Table 1.5 Phrases with highest χ2 and used by Wenwui Daily in each year and quarter