# Does Weather Matter? Causal Analysis of TV Logs

## TL;DR

This paper presents a causal analysis demonstrating how weather attributes like pressure and precipitation significantly influence TV watching patterns, filling a research gap in understanding weather's impact on media consumption.

## Contribution

It introduces the first large-scale causal study examining the effect of weather on TV watching behaviors, highlighting specific weather factors that cause notable changes.

## Key findings

- Pressure and precipitation significantly affect TV watching patterns
- Weather attributes cause major changes in viewing behaviors
- First large-scale causal analysis of weather's impact on TV viewing

## Abstract

Weather affects our mood and behaviors, and many aspects of our life. When it is sunny, most people become happier; but when it rains, some people get depressed. Despite this evidence and the abundance of data, weather has mostly been overlooked in the machine learning and data science research. This work presents a causal analysis of how weather affects TV watching patterns. We show that some weather attributes, such as pressure and precipitation, cause major changes in TV watching patterns. To the best of our knowledge, this is the first large-scale causal study of the impact of weather on TV watching patterns.