Summary of your 'study carrel' ============================== This is a summary of your Distant Reader 'study carrel'. The Distant Reader harvested & cached your content into a collection/corpus. It then applied sets of natural language processing and text mining against the collection. The results of this process was reduced to a database file -- a 'study carrel'. The study carrel can then be queried, thus bringing light specific characteristics for your collection. These characteristics can help you summarize the collection as well as enumerate things you might want to investigate more closely. This report is a terse narrative report, and when processing is complete you will be linked to a more complete narrative report. Eric Lease Morgan Number of items in the collection; 'How big is my corpus?' ---------------------------------------------------------- 1 Average length of all items measured in words; "More or less, how big is each item?" ------------------------------------------------------------------------------------ 2448 Average readability score of all items (0 = difficult; 100 = easy) ------------------------------------------------------------------ 106 Top 50 statistically significant keywords; "What is my collection about?" ------------------------------------------------------------------------- 1 Mamma 1 Johnny Top 50 lemmatized nouns; "What is discussed?" --------------------------------------------- 12 soup 12 day 9 man 8 thumb 8 hare 8 boy 5 thing 5 sky 5 moor 5 head 5 hand 5 gun 5 fun 4 table 4 face 4 child 4 chair 4 cat 4 arm 3 umbrella 3 today 3 spectacle 3 scissor 3 river 3 pussy 3 picture 3 one 3 nose 3 match 3 leg 3 hop 3 hair 3 fish 3 fellow 3 eye 3 dog 3 coffee 3 clothe 3 book 2 writing 2 wind 2 way 2 tree 2 toy 2 toe 2 time 2 tailor 2 tail 2 sun 2 shock Top 50 proper nouns; "What are the names of persons or places?" -------------------------------------------------------------- 18 Johnny 11 Mamma 8 Story 7 Philip 5 ow 5 Frederick 4 Tray 4 Harriet 4 Conrad 4 Black 4 Augustus 3 Papa 3 Head 3 Agrippa 2 _ 2 William 2 STRUWWELPETER 2 Robert 2 Phil 2 Peter 2 Nurse 2 Merry 2 Little 2 Hare 2 Fred 2 Christmas 2 Bob 2 Arthur 2 Alack 1 twas 1 toys-- 1 swam 1 sup-- 1 rage-- 1 mew-- 1 hiss 1 hair-- 1 fidgety 1 by-- 1 box 1 aim 1 York 1 Warne 1 Transcriber 1 Team 1 Stories 1 Stared 1 Soup 1 Silly 1 Ran Top 50 personal pronouns nouns; "To whom are things referred?" ------------------------------------------------------------- 54 he 32 they 21 him 19 me 19 it 16 you 15 she 14 i 5 her 4 them 2 we 2 himself Top 50 lemmatized verbs; "What do things do?" --------------------------------------------- 65 be 26 have 25 see 16 do 14 go 14 come 12 say 12 cry 11 look 10 take 10 make 9 burn 8 scream 7 run 7 fall 6 tell 6 grow 5 suck 5 shoot 5 laugh 5 hear 4 think 4 stand 4 snip 4 sit 4 lie 4 get 4 fly 4 catch 3 whip 3 try 3 touch 3 let 3 leave 3 know 3 head 3 find 3 drink 3 call 2 wet 2 watch 2 walk 2 wag 2 understand 2 turn 2 tumble 2 tease 2 tear 2 stretch 2 stop Top 50 lemmatized adjectives and adverbs; "How are things described?" --------------------------------------------------------------------- 22 so 19 out 18 little 12 up 12 not 11 now 10 very 10 then 10 poor 9 never 8 good 8 black 7 there 7 more 7 great 7 away 7 again 6 red 6 naughty 6 all 5 too 5 still 5 over 5 nasty 5 here 5 down 5 as 4 quite 4 on 4 off 4 nice 4 just 4 high 4 green 4 always 3 tall 3 silly 3 sad 3 pretty 3 only 3 once 3 often 3 last 3 everywhere 3 dear 3 cruel 3 close 2 yet 2 worse 2 wet Top 50 lemmatized superlative adjectives; "How are things described to the extreme?" ------------------------------------------------------------------------- 1 clever Top 50 lemmatized superlative adverbs; "How do things do to the extreme?" ------------------------------------------------------------------------ Top 50 Internet domains; "What Webbed places are alluded to in this corpus?" ---------------------------------------------------------------------------- Top 50 URLs; "What is hyperlinked from this corpus?" ---------------------------------------------------- Top 50 email addresses; "Who are you gonna call?" ------------------------------------------------- Top 50 positive assertions; "What sentences are in the shape of noun-verb-noun?" ------------------------------------------------------------------------------- 1 cats did mew-- 1 chair falls over 1 child growing still 1 conrad cries out 1 day went out 1 gun shot cup 1 hare sits snug 1 mamma comes home 1 mamma did fret 1 mamma had scarcely 1 mamma look quite 1 mamma looked very 1 soup get cold 1 thing is plain 1 thumb was in 1 thumbs are off 1 tray came out 1 tray grew very 1 tray is happy Top 50 negative assertions; "What sentences are in the shape of noun-verb-no|not-noun?" --------------------------------------------------------------------------------------- A rudimentary bibliography -------------------------- id = 12116 author = Hoffmann, Heinrich title = Struwwelpeter: Merry Stories and Funny Pictures date = keywords = Johnny; Mamma summary = He caught the flies, poor little things, And whipped poor Tray till he was sore, Mamma and Nurse went out one day "Boys, leave the Black-a-moor alone! The Story of the Man that went out Shooting The little hare came, hop, hop, hop, He cries and screams and runs away; The Story of Little Suck-a-Thumb One day Mamma said "Conrad dear, To little boys who suck their thumbs; And caught out little Suck-a-Thumb. Mamma comes home: there Conrad stands, "Ah!" said Mamma, "I knew he''d come To naughty little Suck-a-Thumb." Next day, now look, the picture shows Look at him, now the fourth day''s come! The Story of Johnny Head-in-Air "Look at little Johnny there, Little Johnny Head-In-Air!" Came a little dog one day; Headlong in poor Johnny fell. And, to tease poor Johnny, said "Silly little Johnny, look, All good little girls and boys No one heard his screams and cries;