Matching multiple search criteria (Unlisting a nested dataset, take 2)

Thanks all for your patience. Here?s a second go that is perhaps more
explicative of what it is I am trying to accomplish (and hopefully in plain
text form)...


I?m using the following packages: tidyverse, purrr, tidytext


I have a number of tweets in the following form:


th <- structure(list(status_id = c("x1047841705729306624",
"x1046966595610927105",

"x1047094786610552832", "x1046988542818308097", "x1046934493553221632",

"x1047227442899775488"), created_at = c("2018-10-04T13:31:45Z",

"2018-10-02T03:34:22Z", "2018-10-02T12:03:45Z", "2018-10-02T05:01:35Z",

"2018-10-02T01:26:49Z", "2018-10-02T20:50:53Z"), text = c("Technique is
everything with olympic lifts ! @ Body By John https://t.co/UsfR6DafZt",

"@Subtronics just went back and rewatched ur FBlice with ur CDJs and let
me tell you man. You are the fucking messiah",

"@ic4rus1 Opportunistic means short-game. As in getting drunk now vs. not
being hung over tomorrow vs. not fucking up your life ten years later.",

"I tend to think about my dreams before I sleep.", "@MichaelAvenatti
@SenatorCollins So, if your client was in her 20s, attending parties with
teenagers, doesn't that make her at the least immature as hell, or at the
worst, a pedophile and a person contributing to the delinquency of minors?",

"i wish i could take credit for this"), lat = c(43.6835853, 40.284123,

37.7706565, 40.431389, 31.1688935, 33.9376735), lng = c(-70.3284118,

-83.078589, -122.4359785, -79.9806895, -100.0768885, -118.130426

), county_name = c("Cumberland County", "Delaware County", "San Francisco
County",

"Allegheny County", "Concho County", "Los Angeles County"), fips =
c(23005L,

39041L, 6075L, 42003L, 48095L, 6037L), state_name = c("Maine",

"Ohio", "California", "Pennsylvania", "Texas", "California"),

state_abb = c("ME", "OH", "CA", "PA", "TX", "CA"), urban_level = c("Medium
Metro",

"Large Fringe Metro", "Large Central Metro", "Large Central Metro",

"NonCore (Nonmetro)", "Large Central Metro"), urban_code = c(3L,

2L, 1L, 1L, 6L, 1L), population = c(277308L, 184029L, 830781L,

1160433L, 4160L, 9509611L)), class = c("data.table", "data.frame"

), row.names = c(NA, -6L), .internal.selfref = )


I also have a number of search terms in the following form:


st <- structure(list(terms = c("me abused depressed", "me hurt depressed",

"feel hopeless depressed", "feel alone depressed", "i feel helpless",

"i feel worthless")), row.names = c(NA, -6L), class = c("tbl_df",

"tbl", "data.frame?))


I am trying to isolate the tweets that contain all of the words in each of
the search terms, i.e ?me? ?abused? and ?depressed? from the first example
search term, but they do not have to be in order or even next to one
another.


I am familiar with the dplyr suite of tools and have been attempting to
generate some sort of ?filter()? to do this. I am not very familiar with
purrr, but there may be a solution using the map function? I have also
explored the tidytext ?unnest_tokens? function which transforms the ?th?
data in the following way:

tidytext::unnest_tokens(th, word, text, token = "tweets") -> tt

head(tt)

status_id created_at lat lng

1: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

2: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

3: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

4: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

5: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

6: x1047841705729306624 2018-10-04T13:31:45Z 43.68359 -70.32841

county_name fips state_name state_abb urban_level urban_code

1: Cumberland County 23005 Maine ME Medium Metro 3

2: Cumberland County 23005 Maine ME Medium Metro 3

3: Cumberland County 23005 Maine ME Medium Metro 3

4: Cumberland County 23005 Maine ME Medium Metro 3

5: Cumberland County 23005 Maine ME Medium Metro 3

6: Cumberland County 23005 Maine ME Medium Metro 3

population word

1: 277308 technique

2: 277308 is

3: 277308 everything

4: 277308 with

5: 277308 olympic

6: 277308 lifts


but once I have unnested the tokens, I am unable to recombine them back
into tweets.


Ideally the end result would append a new column to the ?th? data that
would flag a tweet that contained all of the search words for any of the
search terms; so the work flow would look like

1) look for all search words for one search term in a tweet

2) if all of the search words in the search term are found, create a flag
(mutate(flag = 1) or some such)

3) do this for all of the tweets

4) move on the next search term and repeat


Again, my thanks for your patience.


--


Nate Parsons

Pronouns: He, Him, His

Graduate Teaching Assistant

Department of Sociology

Portland State University

Portland, Oregon


503-725-9025

503-725-3957 FAX