## ----load_instagram, eval=FALSE------------------------------------------
#  library(instaR)

## ----insta_auth, eval=FALSE----------------------------------------------
#  my_oauth <- instaOAuth(app_id="1f1f8228974248ba804b4c02fb3c082f", app_secret="a8a727a6b21e488988207686c88ec49e")
#  save(my_oauth, file="my_oauth")

## ----load_clarifai, eval=FALSE-------------------------------------------
#  library(clarifai)

## ----get_data, eval=FALSE------------------------------------------------
#  filepath <- system.file("inst/extdata/congress.csv", package = "clarifai")
#  pols <- read.csv(filepath)

## ----download_data, eval=FALSE-------------------------------------------
#  # getUserMedia(pols$instagram[1], token=my_oauth)
#  
#  res <- list()
#  for (i in 1:nrow(pols)) {
#  	# Not all politicians have instagram accounts.
#  	if (pols$instagram[i]!="") {
#  		# Not all have public posts
#  		res[[i]] <- tryCatch(getUserMedia(pols$instagram[i], token=my_oauth), error=function(err) NA)
#  	} else {
#  		res[[i]] <- NA
#  	}
#  }
#  # rbind
#  res2 <- do.call(rbind, res) # nrow = 8088 (may change for runs in the future)

## ----merge_write, eval=FALSE---------------------------------------------
#  
#  # Get pols data ready
#  small_pols <- pols[,c("first_name", "last_name", "party", "instagram", "dw_nominate")]
#  small_pols_2 <- subset(small_pols, instagram!="") # take out no username/NA
#  
#  # Merge
#  res2[, c("first_name", "last_name", "party", "instagram", "dw_nominate")] <-
#  small_pols_2[match(res2$username, small_pols_2$instagram),]
#  
#  # write.csv(res2, file="res2.csv", row.names=F)

## ----get_clarifai_labels, eval=FALSE-------------------------------------
#  
#  labs <- list()
#  # Not implemented optimally.
#  # You can push all images at once. And that is the best than 8k requests.
#  for (i in 1:nrow(res2)) {
#  	labs[[i]] <- tryCatch(tag_image_urls(res2$image_url[i]), error=function(err) NA)	
#  }
#  
#  labs_df <- do.call(rbind, labs)

## ----merge_and_save, eval=FALSE------------------------------------------
#  
#  # Merge
#  labs_df[,names(res2)] <- res2[match(labs_df$img_url, res2$image_url),]
#  
#  # write.csv(labs_df, file="labs_df.csv", row.names=F)
#  # This data frame is available in the extdata folder

## ----pop_tags, eval=FALSE------------------------------------------------
#  head(table(labs_df$tags)[order(-table(labs_df$tags))], 40)

## ----out_pop, eval=FALSE-------------------------------------------------
#  ## people    politics       adult         men       group  government    business       women    portrait      leader
#  ##       1592        1137        1132         999         910         795         793         773         763         670
#  ##   clothing  politician   education      speech    election     indoors     meeting        room competition        many
#  ##        554         472         456         435         433         426         360         352         347         345

## ----military, eval=FALSE------------------------------------------------
#  table(grepl("military", labs_df$tags), labs_df$party)

## ----out_mil, eval=FALSE-------------------------------------------------
#  ##           D     R
#  ##  FALSE 19806 16030
#  ##  TRUE     94    90
#  

## ----women, eval=FALSE---------------------------------------------------
#  table(grepl("women", labs_df$tags), labs_df$party)

## ----out_women, eval=FALSE-----------------------------------------------
#  ##           D     R
#  ##  FALSE 19458 15853
#  ##  TRUE    442   267

## ----men, eval=FALSE-----------------------------------------------------
#  table(grepl("men", labs_df$tags), labs_df$party)

## ----out_men, eval=FALSE-------------------------------------------------
#  ##            D     R
#  ##  FALSE 18265 14978
#  ##  TRUE   1635  1142

## ----protest, eval=FALSE-------------------------------------------------
#  table(grepl("protest", labs_df$tags), labs_df$party)

## ----out_protest, eval=FALSE---------------------------------------------
#  
#  ##           D     R
#  ##  FALSE 19734 16024
#  ##  TRUE    166    96