R/poster.Rmd

---
title: "News from the International Comparable Corpus"
subtitle: "First launch of ICC written"
date: "`r Sys.Date()`"
author:
    - name: Marc Kupietz
      affil: 1
    - name: Adrien Barbaresi
      affil: 2
    - name: Anna Čermáková
      affil: 3
    - name: Małgorzata Czachor
      affil: 4
    - name: Nils Diewald
      affil: 1
    - name: Jarle Ebeling
      affil: 5
    - name: Rafał L. Górski
      affil: 4
    - name: John Kirk
      affil: 6
    - name: Michal Křen
      affil: 3
    - name: Harald Lüngen
      affil: 1
    - name: Eliza Margaretha
      affil: 1
    - name: Signe Oksefjell Ebeling
      affil: 5
    - name: Mícheál Ó Meachair
      affil: 7
    - name: Ines Pisetta
      affil: 1
    - name: Elaine Uí Dhonnchadha
      affil: 8
    - name: Friedemann Vogel
      affil: 9
    - name: Rebecca Wilm
      affil: 1
    - name: Jiajin Xu
      affil: 10
    - name: Rameela Yaddehige
      affil: 1
affiliation:
  - num: 1
    address: IDS Mannheim
  - num: 2
    address: BBAW Berlin
  - num: 3
    address: Charles University
  - num: 4
    address: Polish Academy of Sciences
  - num: 5
    address: University of Oslo
  - num: 6
    address: University of Vienna
  - num: 7
    address: Dublin City University
  - num: 8
    address: Trinity College Dublin
  - num: 9
    address: University of Siegen
  - num: 10
    address: Beijing Foreign Studies University


logoleft_name: "../Figures/ICC_COL.svg"
author_textsize: "32pt"

contact:
  email: icc@ids-manneim.de
  website: https://www.ids-mannheim.de/digspra/kl
  qrlink: >
    `r posterdown::qrlink("https://korap.ids-mannheim.de/instance/icc", "icc-logo-whitebg.svg")`

output:
  posterdown::posterdown_ids:
        self_contained: false
        keep_md: true

bibliography: ../tex/references.bib
csl: "https://raw.githubusercontent.com/ICLC-10/Zotero/master/styles/ICLC-10.csl"
---

```{r setup, include=FALSE, echo=FALSE, warning=FALSE}
knitr::opts_chunk$set(dev = 'svg', echo = FALSE, warnings = FALSE)
source("common.R")
```
# ICC aims & charcteristics

* make available comparable corpora  of many languages for contrastive linguistic research [@kirk_ice_2017]
* mostly based on existing corpora
* ICC has a pre-defined “balanced” composition
  * based on the one of the ICE [@greenbaum_comparing_1996]

# Current launch of ICC written

* written parts for Chinese, Czech, English, German, Irish (partly), Norwegian publicly available
  * partially including UDPipe 2.0 annotations [@straka_udpipe_2018]
  * via Corpus Workbench or KorAP [@diewald_korap_2016]
  
  * usable via Corpus Workbench or KorAP [@diewald_korap_2016]

```{r korap-query, fig.cap="KorAP UI for ICC-GER and ICC-NOR, showing annotation queries and layers, as well as a virtual corpus definition, based on ICC genre and publication date metadata."}
knitr::include_graphics("korap_query_ger-nor.svg")
```

## Composition of the ICC parts 

```{r composition-by-genre, fig.cap="Actual composition of selected ICC parts with respect to ICC domain. (For the other ICC parts, the ICC genre metadatum was not yet accessible via the API at the editorial deadline.)", message = FALSE, fig.width=14, fig.height=10, out.width = "100%"}
icc_genre <- icc %>%
  expand_grid(genre) %>%
  mutate(vc = paste0("iccGenre=", genre)) %>%
  rowwise() %>%
  mutate(tokens= corpusStats(icc_con(lang, token), vc = vc)@tokens)

icc_genre %>% ggplot(aes(x=lang, fill=genre, y=tokens)) +
  geom_col() + scale_y_continuous(labels = label_number(scale_cut = cut_short_scale())) +
  theme_ids(base_size = 24) +
  theme(
    axis.title.x = element_text(size = rel(1.5), face = "bold"),
    axis.title.y = element_text(size = rel(1.5), face = "bold"),
     axis.text = element_text(size = rel(0.70)),
    legend.title = element_text(size = rel(0.85), face = "bold"),
    legend.text = element_text(size = rel(1))) +
  scale_fill_ids() +
  geom_text(aes(label=if_else(tokens > 0, as.character(tokens), ""), y=tokens), position= position_stack(reverse = F, vjust = 0.5), color="black", size=6.2, family="Fira Sans Condensed")

```


```{r composition-by-pubdate, fig.cap="Composition of the selected ICC parts with respect to year of publication.", message=F, warning=F, fig.width=14, fig.height=3, out.width = "80%"}
year <- c(1986:2023)

icc_year <- icc %>%
  expand_grid(year) %>%
  mutate(vc = paste0("pubDate in ", year)) %>%
  rowwise() %>%
  mutate(tokens= corpusStats(icc_con(lang, token), vc = vc)@tokens)

icc_year %>% ggplot(aes(x=year, fill=lang, color=lang, y=tokens)) +
  # geom_smooth(se=F, span=0.25) +
  xlim(1990, 2023) +
  ylim(0, NA) +
  stat_smooth(
        geom = 'area', method = 'loess', span = 1/4,
        alpha = 0.1) +
  # geom_area(alpha=0.1,  position = "identity") +
  scale_fill_ids() + scale_colour_ids() + 
  scale_y_continuous(labels = label_number(scale_cut = cut_short_scale())) +
  theme_ids(base_size=24) + 
    theme(
    axis.title.x = element_text(size = rel(1.5), face = "bold"),
    axis.title.y = element_text(size = rel(1.5), face = "bold"),
     axis.text = element_text(size = rel(1)),
    legend.title = element_text(size = rel(1), face = "bold"),
    legend.text = element_text(size = rel(1))) 
```


# Pilot study

* Identification of Light Verb Constructions with *take*
* in order to investigate the limitations imposed by the very small corpus sizes
* using RKorapClient [@kupietz_rkorapclient_2020] to access corpora and get reproducible results of the collocation analysis


```{r take-icc, echo=TRUE, fig.cap="Collocation analysis of *take* using the RKorAPClient package for R"}
take_ca_icc <-
  collocationAnalysis(
    icc_con("eng"),
    "focus({[ud/l=take]} [ud/p=NOUN])",
    leftContextSize = 0,
    rightContextSize = 1,
    minOccur = 2,
    addExamples = T
  )

take_ca_icc %>% show_table()
```

## Results

* for English the query for *take* + NOUN (as direct right neighbour) yields 10 different pairs with a minimum frequency of 2 (see  Figure \@ref(fig:take-icc))
  * based English Wikipedia (2015) the query yields 139 pairs (log-dice-threshold: 2.0) with about 20 false positives
* for ICC German with DeReKo as background corpus, the ratio of true positive LVCs is 10/80 

# Summary & Outlook

* we have made available corpora of 4+ languages available for contrastive research
* however, even with quite frequent phenomena, the results on the small corpora are to be used with caution
  * typically they need to be verified on larger monolingual corpora
* the uniform acces is in any case helpful for contrastive studies
* ICC also serves as a crystallization point for larger corpora and complementary approaches such as EuReCo

# References