Media Slant: Slant Contagion and Polarization

Here, we replicate Table 4, but instead of pre-FNC/MSNBC era newspaper endorsements, we distinguish observations by the county-level Republican vote share terciles


This content originally appeared on HackerNoon and was authored by Tech Media Bias [Research Publication]

Abstract and 1 Introduction 2. Data

3. Measuring Media Slant and 3.1. Text pre-processing and featurization

3.2. Classifying transcripts by TV source

3.3. Text similarity between newspapers and TV stations and 3.4. Topic model

4. Econometric Framework

4.1. Instrumental variables specification

4.2. Instrument first stage and validity

5. Results

5.1. Main results

5.2. Robustness checks

6. Mechanisms and Heterogeneity

6.1. Local vs. national or international news content

6.2. Cable news media slant polarizes local newspapers

7. Conclusion and References

\ Online Appendices

A. Data Appendix

A.1. Newspaper articles

A.2. Alternative county matching of newspapers and A.3. Filtering of the article snippets

A.4. Included prime-time TV shows and A.5. Summary statistics

B. Methods Appendix, B.1. Text pre-processing and B.2. Bigrams most predictive for FNC or CNN/MSNBC

B.3. Human validation of NLP model

B.4. Distribution of Fox News similarity in newspapers and B.5. Example articles by Fox News similarity

B.6. Topics from the newspaper-based LDA model

C. Results Appendix

C.1. First stage results and C.2. Instrument exogeneity

C.3. Placebo: Content similarity in 1995/96

C.4. OLS results

C.5. Reduced form results

C.6. Sub-samples: Newspaper headquarters and other counties and C.7. Robustness: Alternative county matching

C.8. Robustness: Historical circulation weights and C.9. Robustness: Relative circulation weights

C.10. Robustness: Absolute and relative FNC viewership and C.11. Robustness: Dropping observations and clustering

C.12. Mechanisms: Language features and topics

C.13. Mechanisms: Descriptive Evidence on Demand Side

C.14. Mechanisms: Slant contagion and polarization

C.14. Mechanisms: Slant contagion and polarization

Here, we replicate Table 4, but instead of pre-FNC/MSNBC era newspaper endorsements, we distinguish observations by the county-level Republican vote share terciles (lowest tercile in the first column, second tercile in middle, and highest tercile in the last column). Qualitatively, we find the same pattern: The relative FNC exposure coefficient is negative in the first column, positive plus relatively small in the second column (coefficients in columns 1 and 2 are not significant), before turning significant, positive, and large in the last column.

\ Notes: 2SLS estimates. Cross-section with newspaper-county-level observations weighted by newspaper circulation in each county. The dependent variable is newspaper language similarity with FNC (the average probability that a snippet from a newspaper is predicted to be from FNC). The righthand side variable of interest is instrumented FNC viewership relative to averaged CNN and MSNBC viewership. Column 1 only includes newspaper-county-level observations from counties where the Republican votes share in 1996 (pre-FNC era) lies in the lowest tercile. In column 2, we include observations from counties in the second tercile, and in column 3 from those in the highest tercile. All columns include state fixed effects, demographic controls as listed in Appendix Table A.2, channel controls (population shares with access to each of the three TV channels), and generic newspaper language features (vocabulary size, avg. word length, avg. sentence length, avg. article length). Standard errors are multiway-clustered at the county and at the newspaper level (in parenthesis): * p < 0.1, ** p < 0.05, *** p < 0.01.

\ Notes: Reduced form estimates. Cross-section with newspaper-county-level observations weighted by newspaper circulation in each county. The dependent variable is newspaper language similarity with FNC (the average probability that a snippet from a newspaper is predicted to be from FNC). The two righthand side variables of interest are (i) the absolute position of FNC viewership (Position FNC) and the (ii) average of the absolute positions of CNN and MSNBC (Position 0.5(CNN+MSNBC)). In column 1 we only include newspapers that endorsed the Democratic Presidential candidate in 1996 (pre-FNC era). In column 2, we focus on newspapers that did not endorse either candidate (or for which endorsement data is not available). Column 3 considers only newspapers that endorsed the Republican candidate. All columns include state fixed effects, demographic controls as listed in Appendix Table A.2, channel controls (population shares with access to each of the three TV channels), and generic newspaper language features (vocabulary size, avg. word length, avg. sentence length, avg. article length). Standard errors are multiway-clustered at the county and at the newspaper level (in parenthesis): * p < 0.1, ** p < 0.05, *** p < 0.01.

\

:::info This paper is available on arxiv under CC 4.0 license.

:::

:::info Authors:

(1) Philine Widmer, ETH Zürich and philine.widmer@gess.ethz.ch;

(2) Sergio Galletta, ETH Zürich and sergio.galletta@gess.ethz.ch;

(3) Elliott Ash, ETH Zürich and ashe@ethz.ch.

:::

\


This content originally appeared on HackerNoon and was authored by Tech Media Bias [Research Publication]


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