Flatten a deeply nested and badly formatted JSON file

Question

I'm pulled some twitter data using tweepy and what I got from there wasn't the most well-formatted json, but I can't quite figure out a way to do it that doesn't take me hours for a single file. (I have about half a million lines of twitter data across about 100 files).

Attached below this is an example of one (1) line of my json file.

Here's a drive link to one of my smaller files if that helps.

Literally any way to do this would be appreciated.

Thanks!

{"created_at":"Thu Feb 07 10:58:27 +0000 2019","id":1093464000120016896,"id_str":"1093464000120016896","text":"RT @sethia_b: @nparama1951 @RBhamaria @jyotsnavarma9 @JaganNKaushik @DineshA58 @Am_dilip @ashvinn15 @SChakram @Savitritvs @Satishrathod100\u2026","source":"\u003ca href=\"http://twitter.com/download/android\" rel=\"nofollow\"\u003eTwitter for Android\u003c/a\u003e","truncated":false,"in_reply_to_status_id":null,"in_reply_to_status_id_str":null,"in_reply_to_user_id":null,"in_reply_to_user_id_str":null,"in_reply_to_screen_name":null,"user":{"id":1070710084441784320,"id_str":"1070710084441784320","name":"Kumaran","screen_name":"Kumaran92023000","location":null,"url":null,"description":null,"translator_type":"none","protected":false,"verified":false,"followers_count":222,"friends_count":427,"listed_count":0,"favourites_count":6036,"statuses_count":6834,"created_at":"Thu Dec 06 16:02:31 +0000 2018","utc_offset":null,"time_zone":null,"geo_enabled":false,"lang":"en","contributors_enabled":false,"is_translator":false,"profile_background_color":"F5F8FA","profile_background_image_url":"","profile_background_image_url_https":"","profile_background_tile":false,"profile_link_color":"1DA1F2","profile_sidebar_border_color":"C0DEED","profile_sidebar_fill_color":"DDEEF6","profile_text_color":"333333","profile_use_background_image":true,"profile_image_url":"http://pbs.twimg.com/profile_images/1070712098160705542/02c6-KwM_normal.jpg","profile_image_url_https":"https://pbs.twimg.com/profile_images/1070712098160705542/02c6-KwM_normal.jpg","profile_banner_url":"https://pbs.twimg.com/profile_banners/1070710084441784320/1544112886","default_profile":true,"default_profile_image":false,"following":null,"follow_request_sent":null,"notifications":null},"geo":null,"coordinates":null,"place":null,"contributors":null,"retweeted_status":{"created_at":"Thu Feb 07 09:02:19 +0000 2019","id":1093434772070658048,"id_str":"1093434772070658048","text":"@nparama1951 @RBhamaria @jyotsnavarma9 @JaganNKaushik @DineshA58 @Am_dilip @ashvinn15 @SChakram @Savitritvs\u2026 https://t.co/lfjAiatkbP","display_text_range":[117,140],"source":"\u003ca href=\"http://twitter.com/download/android\" rel=\"nofollow\"\u003eTwitter for Android\u003c/a\u003e","truncated":true,"in_reply_to_status_id":1093433827501006848,"in_reply_to_status_id_str":"1093433827501006848","in_reply_to_user_id":2783847553,"in_reply_to_user_id_str":"2783847553","in_reply_to_screen_name":"nparama1951","user":{"id":796185239370379264,"id_str":"796185239370379264","name":"B.Sethia","screen_name":"sethia_b","location":null,"url":null,"description":"Nation First: Followed by Hollywood Celebrity Paris Hilton, NSitharamanOffice Dr UditRaj MP :\n Views - Contrarian :\n\nFollow Back\nRT not endorsement","translator_type":"none","protected":false,"verified":false,"followers_count":3237,"friends_count":2315,"listed_count":8,"favourites_count":71196,"statuses_count":56458,"created_at":"Wed Nov 09 02:58:48 +0000 2016","utc_offset":null,"time_zone":null,"geo_enabled":true,"lang":"en","contributors_enabled":false,"is_translator":false,"profile_background_color":"F5F8FA","profile_background_image_url":"","profile_background_image_url_https":"","profile_background_tile":false,"profile_link_color":"1DA1F2","profile_sidebar_border_color":"C0DEED","profile_sidebar_fill_color":"DDEEF6","profile_text_color":"333333","profile_use_background_image":true,"profile_image_url":"http://pbs.twimg.com/profile_images/1053957260974542848/RrRuZL1g_normal.jpg","profile_image_url_https":"https://pbs.twimg.com/profile_images/1053957260974542848/RrRuZL1g_normal.jpg","profile_banner_url":"https://pbs.twimg.com/profile_banners/796185239370379264/1531817659","default_profile":true,"default_profile_image":false,"following":null,"follow_request_sent":null,"notifications":null},"geo":null,"coordinates":null,"place":null,"contributors":null,"is_quote_status":false,"extended_tweet":{"full_text":"@nparama1951 @RBhamaria @jyotsnavarma9 @JaganNKaushik @DineshA58 @Am_dilip @ashvinn15 @SChakram @Savitritvs @Satishrathod100 @banerji1 @ramakirao @RaghavendraUp16 @ads7506 @Kumaran92023000 @kjayashree31 @gouranga1964 @SureshanDelhi @ravi_sec @faramroze @kavita_tewari @kailashkaushik8 @pushprajdumraon @FatyachandJ @sukumaranlens @Hydbiryani11 @ChaudhrGurnam @DurgaMaddikonda @ShibaBhanja @aarjeekaykannan @singhsantosh98 @badi_mishra @LighteningBolt9 @birajanath @sn_ojha @Speakwithsence1 @dharmvirjangra9 @LillyMaryPinto @RohiniShah73 @postcard_news @MailOnline @EconomicTimes @narendramodi @BJP4India @AmitShah @TarekFatah @TrueIndology @republic @TelegraphTech 10 Naxals killed in encounter with security forces in Chhattisgarh","display_text_range":[665,731],"entities":{"hashtags":[],"urls":[],"user_mentions":[{"screen_name":"nparama1951","name":"N.Paramasivam","id":2783847553,"id_str":"2783847553","indices":[0,12]},{"screen_name":"RBhamaria","name":"Capt. Ritesh Bhamaria \ud83c\uddee\ud83c\uddf3 \ud83c\udde6\ud83c\uddfa","id":326234086,"id_str":"326234086","indices":[13,23]},{"screen_name":"jyotsnavarma9","name":"Jyotsna Varma \ud83c\uddee\ud83c\uddf3","id":3166184569,"id_str":"3166184569","indices":[24,38]},{"screen_name":"JaganNKaushik","name":"JN Kaushik","id":878303278420840448,"id_str":"878303278420840448","indices":[39,53]},{"screen_name":"DineshA58","name":"Dinesh Agarawal","id":741906012194607104,"id_str":"741906012194607104","indices":[54,64]},{"screen_name":"Am_dilip","name":"dilip","id":2475549384,"id_str":"2475549384","indices":[65,74]},{"screen_name":"ashvinn15","name":"Ashwin","id":2877219241,"id_str":"2877219241","indices":[75,85]},{"screen_name":"SChakram","name":"Sudarshan Chakram","id":219893148,"id_str":"219893148","indices":[86,95]},{"screen_name":"Savitritvs","name":"Savitri S","id":954272364849606662,"id_str":"954272364849606662","indices":[96,107]},{"screen_name":"Satishrathod100","name":"Satish 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Iyer","id":3252380094,"id_str":"3252380094","indices":[189,202]},{"screen_name":"gouranga1964","name":"gouranga","id":883271109294137344,"id_str":"883271109294137344","indices":[203,216]},{"screen_name":"SureshanDelhi","name":"psureshan","id":76917843,"id_str":"76917843","indices":[217,231]},{"screen_name":"ravi_sec","name":"Ravi Kiren","id":105771045,"id_str":"105771045","indices":[232,241]},{"screen_name":"faramroze","name":"Faramroze \ud83c\udf31\ud83c\udf3f\ud83c\udf3e","id":1007265900418891777,"id_str":"1007265900418891777","indices":[242,252]},{"screen_name":"kavita_tewari","name":"kavi \ud83c\uddee\ud83c\uddf3\ud83c\uddee\ud83c\uddf3","id":2952276812,"id_str":"2952276812","indices":[253,267]},{"screen_name":"kailashkaushik8","name":"Kailash Kaushik","id":2206428378,"id_str":"2206428378","indices":[268,284]},{"screen_name":"pushprajdumraon","name":"Pushpraj Singh","id":805466304769654785,"id_str":"805466304769654785","indices":[285,301]},{"screen_name":"FatyachandJ","name":"FATYACHAND JETWANI","id":2345449561,"id_str":"2345449561","indices":[302,314]},{"screen_name":"sukumaranlens","name":"Bhairava","id":964091510630297601,"id_str":"964091510630297601","indices":[315,329]},{"screen_name":"Hydbiryani11","name":"sanatanadharmi","id":791069964434276357,"id_str":"791069964434276357","indices":[330,343]},{"screen_name":"ChaudhrGurnam","name":"Air Mshl GSChaudhry PVSM, AVSM,VSM","id":801423504352514048,"id_str":"801423504352514048","indices":[344,358]},{"screen_name":"DurgaMaddikonda","name":"Kanaka Durga Prasad Maddikonda","id":971373447757619200,"id_str":"971373447757619200","indices":[359,375]},{"screen_name":"ShibaBhanja","name":"Shiba Prasad Bhanja","id":1045647290084413440,"id_str":"1045647290084413440","indices":[376,388]},{"screen_name":"aarjeekaykannan","name":"r g kannan","id":1127245123,"id_str":"1127245123","indices":[389,405]},{"screen_name":"singhsantosh98","name":"Santosh Singh","id":947123021495525376,"id_str":"947123021495525376","indices":[406,421]},{"screen_name":"badi_mishra","name":"Satya badi Mishra","id":1068305802245459968,"id_str":"1068305802245459968","indices":[422,434]},{"screen_name":"LighteningBolt9","name":"LightningBolt\u274c#MaymustGo","id":963238016457347072,"id_str":"963238016457347072","indices":[435,451]},{"screen_name":"birajanath","name":"Chaiwala Bhakt #RSS #BadHindu","id":113578227,"id_str":"113578227","indices":[452,463]},{"screen_name":"sn_ojha","name":"Dr S N Ojha\ud83c\uddee\ud83c\uddf3","id":560927596,"id_str":"560927596","indices":[464,472]},{"screen_name":"Speakwithsence1","name":"Speakwithsense","id":964835386403860482,"id_str":"964835386403860482","indices":[473,489]},{"screen_name":"dharmvirjangra9","name":"\u0927\u0930\u094d\u092e\u0935\u0940\u0930 \u092c\u094c\u0928\u094d\u0926\u0935\u093e\u0932","id":3369674594,"id_str":"3369674594","indices":[490,506]},{"screen_name":"LillyMaryPinto","name":"Lilly \u0932\u093f\u0932\u094d\u0932\u0940 \u0cb2\u0cbf\u0cb2\u0ccd\u0cb2\u0cbf \ud83c\uddee\ud83c\uddf3","id":2801729758,"id_str":"2801729758","indices":[507,522]},{"screen_name":"RohiniShah73","name":"Rohini Shah \ud83c\uddee\ud83c\uddf3","id":3300890464,"id_str":"3300890464","indices":[523,536]},{"screen_name":"postcard_news","name":"Post Card","id":3179331468,"id_str":"3179331468","indices":[537,551]},{"screen_name":"MailOnline","name":"Daily Mail Online","id":15438913,"id_str":"15438913","indices":[552,563]},{"screen_name":"EconomicTimes","name":"EconomicTimes","id":39743812,"id_str":"39743812","indices":[564,578]},{"screen_name":"narendramodi","name":"Narendra Modi","id":18839785,"id_str":"18839785","indices":[579,592]},{"screen_name":"BJP4India","name":"BJP","id":207809313,"id_str":"207809313","indices":[593,603]},{"screen_name":"AmitShah","name":"Amit Shah","id":1447949844,"id_str":"1447949844","indices":[604,613]},{"screen_name":"TarekFatah","name":"Tarek Fatah","id":17537467,"id_str":"17537467","indices":[614,625]},{"screen_name":"TrueIndology","name":"True Indology","id":4472065032,"id_str":"4472065032","indices":[626,639]},{"screen_name":"republic","name":"Republic","id":811972460560019456,"id_str":"811972460560019456","indices":[640,649]},{"screen_name":"TelegraphTech","name":"Telegraph Technology Intelligence","id":19712106,"id_str":"19712106","indices":[650,664]}],"symbols":[]}},"quote_count":0,"reply_count":1,"retweet_count":1,"favorite_count":2,"entities":{"hashtags":[],"urls":[{"url":"https://t.co/lfjAiatkbP","expanded_url":"https://twitter.com/i/web/status/1093434772070658048","display_url":"twitter.com/i/web/status/1\u2026","indices":[109,132]}],"user_mentions":[{"screen_name":"nparama1951","name":"N.Paramasivam","id":2783847553,"id_str":"2783847553","indices":[0,12]},{"screen_name":"RBhamaria","name":"Capt. Ritesh Bhamaria \ud83c\uddee\ud83c\uddf3 \ud83c\udde6\ud83c\uddfa","id":326234086,"id_str":"326234086","indices":[13,23]},{"screen_name":"jyotsnavarma9","name":"Jyotsna Varma \ud83c\uddee\ud83c\uddf3","id":3166184569,"id_str":"3166184569","indices":[24,38]},{"screen_name":"JaganNKaushik","name":"JN Kaushik","id":878303278420840448,"id_str":"878303278420840448","indices":[39,53]},{"screen_name":"DineshA58","name":"Dinesh Agarawal","id":741906012194607104,"id_str":"741906012194607104","indices":[54,64]},{"screen_name":"Am_dilip","name":"dilip","id":2475549384,"id_str":"2475549384","indices":[65,74]},{"screen_name":"ashvinn15","name":"Ashwin","id":2877219241,"id_str":"2877219241","indices":[75,85]},{"screen_name":"SChakram","name":"Sudarshan Chakram","id":219893148,"id_str":"219893148","indices":[86,95]},{"screen_name":"Savitritvs","name":"Savitri S","id":954272364849606662,"id_str":"954272364849606662","indices":[96,107]}],"symbols":[]},"favorited":false,"retweeted":false,"filter_level":"low","lang":"en"},"is_quote_status":false,"quote_count":0,"reply_count":0,"retweet_count":0,"favorite_count":0,"entities":{"hashtags":[],"urls":[],"user_mentions":[{"screen_name":"sethia_b","name":"B.Sethia","id":796185239370379264,"id_str":"796185239370379264","indices":[3,12]},{"screen_name":"nparama1951","name":"N.Paramasivam","id":2783847553,"id_str":"2783847553","indices":[14,26]},{"screen_name":"RBhamaria","name":"Capt. 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Answer 1

This looks like ndjson. The ndjson and the jsonlite packages can both handle it.

dat <- ndjson::stream_in("data/INCIndia26febru.json")
# Source: local data table [1,584 x 2,814]
# 
# # A tibble: 1,584 x 2,814
#    contributors coordinates created_at entities.hashta… entities.symbols entities.urls entities.user_m…
#           <int>       <int> <chr>                 <int>            <int>         <int>            <dbl>
#  1           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  2           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  3           NA          NA Tue Feb 2…               NA               NA            NA          2.23e 8
#  4           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
#  5           NA          NA Tue Feb 2…               NA               NA            NA          1.06e18
#  6           NA          NA Tue Feb 2…               NA               NA            NA          1.47e 8
#  7           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
#  8           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  9           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
# 10           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
# # … with 1,574 more rows, and 2,807 more variables: entities.user_mentions.0.id_str <chr>,
# #   entities.user_mentions.0.indices.0 <dbl>, entities.user_mentions.0.indices.1 <dbl>,
# #   entities.user_mentions.0.name <chr>, entities.user_mentions.1.id <dbl>,
# #   entities.user_mentions.0.screen_name <chr>, entities.user_mentions.1.id_str <chr>,
# #   entities.user_mentions.1.indices.0 <dbl>, retweeted_status.entities.user_mentions.0.name <chr>,
# #   retweeted_status.entities.user_mentions.0.screen_name <chr>,
# #   retweeted_status.extended_tweet.display_text_range.0 <dbl>,
# #   retweeted_status.entities.user_mentions.0.id_str <chr>,
# #   retweeted_status.entities.user_mentions.0.indices.0 <dbl>,
# #   retweeted_status.entities.user_mentions.0.indices.1 <dbl>, retweeted_status.entities.urls.0.url <chr>,
# #   retweeted_status.entities.user_mentions.0.id <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.media_url_https <chr>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.h <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.medium.h <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.resize <chr>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.w <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.indices.0 <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.indices.1 <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.media_url <chr>, in_reply_to_user_id_str <chr>,
# #   in_reply_to_status_id_str <chr>, is_quote_status <lgl>, lang <chr>, id_str <chr>,
# #   in_reply_to_screen_name <chr>, in_reply_to_status_id <dbl>, in_reply_to_user_id <dbl>, retweet_count <dbl>,
# #   place <int>, quote_count <dbl>, retweeted <lgl>, retweeted_status.contributors <int>, reply_count <dbl>,
# #   retweeted_status.coordinates <int>, retweeted_status.created_at <chr>, user.created_at <chr>,
# #   user.contributors_enabled <lgl>, retweeted_status.user.utc_offset <int>,
# #   retweeted_status.user.verified <lgl>, source <chr>, text <chr>, timestamp_ms <chr>, truncated <lgl>,
# #   user.default_profile <lgl>, user.following <int>, user.default_profile_image <lgl>, user.description <chr>,
# #   user.follow_request_sent <int>, user.followers_count <dbl>, user.friends_count <dbl>,
# #   user.favourites_count <dbl>, quoted_status.extended_tweet.extended_entities.media.0.sizes.thumb.resize <chr>,
# #   quoted_status.extended_tweet.extended_entities.media.0.sizes.thumb.w <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.aspect_ratio.0 <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.aspect_ratio.1 <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.type <chr>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.duration_millis <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.variants.0.bitrate <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.url <chr>,
# #   retweeted_status.entities.hashtags.0.indices.0 <dbl>, retweeted_status.entities.hashtags.0.indices.1 <dbl>,
# #   retweeted_status.entities.hashtags.0.text <chr>, favorite_count <dbl>,
# #   entities.user_mentions.1.indices.1 <dbl>, entities.user_mentions.1.name <chr>,
# #   entities.user_mentions.1.screen_name <chr>, favorited <lgl>, filter_level <chr>, geo <int>, id <dbl>,
# #   retweeted_status.favorite_count <dbl>, retweeted_status.favorited <lgl>, retweeted_status.filter_level <chr>,
# #   retweeted_status.extended_tweet.full_text <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.sizes.thumb.resize <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.sizes.thumb.w <dbl>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.type <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.url <chr>, user.id_str <chr>,
# #   user.is_translator <lgl>, user.lang <chr>, user.listed_count <dbl>, user.location <chr>, user.name <chr>,
# #   user.geo_enabled <lgl>, user.id <dbl>, retweeted_status.display_text_range.0 <dbl>,
# #   retweeted_status.display_text_range.1 <dbl>, retweeted_status.entities.hashtags <int>,
# #   retweeted_status.entities.symbols <int>, retweeted_status.entities.urls.0.display_url <chr>,
# #   retweeted_status.entities.urls.0.expanded_url <chr>, retweeted_status.entities.urls.0.indices.0 <dbl>,
# #   retweeted_status.entities.urls.0.indices.1 <dbl>, retweeted_status.geo <int>, …

Or:

dat <- jsonlite::stream_in(file("data/INCIndia26febru.json"))
tibble::glimpse(dat)
# Observations: 1,584
# Variables: 36
# $ created_at                <chr> "Tue Feb 26 13:09:36 +0000 2019", "Tue Feb 26 13:09:38 +0000 2019", "Tue Feb …
# $ id                        <dbl> 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.10038…
# $ id_str                    <chr> "1100382373823299586", "1100382382396448770", "1100382385013645314", "1100382…
# $ text                      <chr> "RT @INCIndia: Congress President @RahulGandhi addresses North-East DCC &amp;…
# $ source                    <chr> "<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for…
# $ truncated                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ in_reply_to_status_id     <dbl> NA, 1.100360e+18, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_status_id_str <chr> NA, "1100359823630237697", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ in_reply_to_user_id       <dbl> NA, 1.153045e+09, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_user_id_str   <chr> NA, "1153045459", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_screen_name   <chr> NA, "INCIndia", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ user                      <data.frame> <data.frame[38 x 39]>
# $ geo                       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ coordinates               <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ place                     <data.frame> <data.frame[38 x 9]>
# $ contributors              <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ retweeted_status          <data.frame> <data.frame[38 x 34]>
# $ is_quote_status           <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, FA…
# $ quote_count               <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ reply_count               <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ retweet_count             <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ favorite_count            <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ entities                  <data.frame> <data.frame[38 x 5]>
# $ favorited                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ retweeted                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ filter_level              <chr> "low", "low", "low", "low", "low", "low", "low", "low", "low", "low", "low", …
# $ lang                      <chr> "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en",…
# $ timestamp_ms              <chr> "1551186576692", "1551186578736", "1551186579360", "1551186579893", "15511865…
# $ display_text_range        <list> [NULL, <23, 100>, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL…
# $ possibly_sensitive        <lgl> NA, NA, NA, NA, FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ quoted_status_id          <dbl> NA, NA, NA, NA, NA, NA, 1.100365e+18, NA, NA, 1.100365e+18, NA, NA, 1.100365e…
# $ quoted_status_id_str      <chr> NA, NA, NA, NA, NA, NA, "1100364859768782849", NA, NA, "1100364859768782849",…
# $ quoted_status             <data.frame> <data.frame[38 x 32]>
# $ quoted_status_permalink   <data.frame> <data.frame[38 x 3]>
# $ extended_tweet            <data.frame> <data.frame[38 x 4]>
# $ extended_entities         <data.frame> <data.frame[38 x 1]>