5."Event construal and temporal distance in natural language" 

"Cognition Data - Twitter next.csv" has cleaned data from tweets in Study 1 regarding mentions of next month/week/year
-RATE is the concreteness rating 
-WEEK is a binary variable if tweet included term "next week"
-MONTH is a binary variable if tweet included term "next month"
-Note that if WEEK = 0 and MONTH = 0 then tweet included term "next year"
-This is cleaned up tweet data (raw data is available by request)
-Drop rate=999 which are tweets with words not in Brysbaert et al. dictionary

"Cognition Data - Twitter YEAR.csv" has cleaned data from tweets in Study 1 regarding mentions of specific years
-RATE is the concreteness rating 
-YEAR inddicates the year that was mentioned
-This is cleaned up tweet data (raw data is available by request)
-Drop rate=999 which are tweets with words not in Brysbaert et al. dictionary

"Cognition Data - NYT holidays.csv" has cleaned data from NYT articles in Study 2 regarding concreteness as a function of distance from holiday
-RATE is the concreteness rating
-DIST is the distance (in days) from holidy
-HOLIDAY specifies the holiday
-This is cleaned up article data (raw data is available by request)
-Drop rate=999 which are tweets with words not in Brysbaert et al. dictionary

"Cognition Data - NYT elections.csv" has cleaned data from NYT articles in Study 2 regarding concreteness as a function of distance from election
-RATE is the concreteness rating
-DIST is the distance (in days) from holidy
-ELECTIONYEAR specifies the election year
-This is cleaned up article data (raw data is available by request)
-Drop rate=999 which are tweets with words not in Brysbaert et al. dictionary