Pular para o conteúdo principal

Controversas e Incongruências na WD - estatísticas

WD de Junho de 2022

# and % and distribution of %, of controversial statements

559,038,971 CLAIMS
132,552,453 potencialmente controversos

23,71%

(base) root@vm096:/home/cloud-di# zcat /app/kgtk/data/wikidata/claims.tsv.gz | wc -l
559,038,972

(base) root@vm096:/home/cloud-di# more /app/kgtk/data/my-tsv/filtered-claims-sorted-uniq.tsv.gz | wc -l
132,552,454

# and % and distribution of % of controversial properties

9,653 PROPERTIES (All)
2,143 potencialmente controversos

22,20 %

Comando

(base) root@vm096:/app/kgtk/temp# cat /app/kgtk/data/my-tsv/all-claims-pred-counted.tsv | wc -l
9654

(base) root@vm096:/app/kgtk/temp# cat /app/kgtk/data/my-tsv/filtered-pred-count-sorted.tsv | wc -l
2144

TOP 10 PROPERTIES (All)

(base) root@vm096:/app/kgtk/temp# kgtk sort -i /app/kgtk/data/my-tsv/all-claims-pred-counted.tsv -c node2 --reverse-columns node2 --numeric-columns node2 / head
node1   label   node2
P31     count   59717980
P1215   count   33122376
P528    count   28738709
P17     count   14996553
P131    count   11371144
P106    count   9608349
P625    count   9267000
P2215   count   8207685
P3083   count   8150658
P6257   count   8091255

TOP 10 PROPERTIES (potencialmente controversos)

(base) root@vm096:/app/kgtk/temp# kgtk sort -i /app/kgtk/data/my-tsv/filtered-pred-count-sorted.tsv  -c node2 --reverse-columns node2 --numeric-columns node2 / head
node1   label   node2
P1215   count   32818006
P528    count   26283488
P2215   count   8207274
P31     count   5407077
P684    count   4306414
P106    count   3987622
P1087   count   2866023
P1082   count   2016139
P361    count   1940350
P527    count   1679292

# and % and distribution of % of qualification for controversial statements

141,983,745 QUALIFICATION FOR CLAIMS (All)
104,362,344 qualificações para algeações potencialmente controversas

87,83 %

Comando

(base) cloud-di@vm096:~$ zcat /app/kgtk/data/my-tsv/quals-sorted.tsv.gz | wc -l
141,983,746

(base) root@vm096:/home/cloud-di# zcat /app/kgtk/data/my-tsv/filtered-quals-sorted.tsv.gz | wc -l
104,362,345

# and % and distribution of % of different qualifiers in controversial statements

9,905 QUALIFIERS (All)
8,700 potencialmente controversos

87,83 %

Comando

(base) root@vm096:/app/kgtk/temp# more /app/kgtk/data/my-tsv/quals-counted.tsv | wc -l
9,907

(base) root@vm096:/app/kgtk/temp# more /app/kgtk/data/my-tsv/filtered-quals-counted.tsv | wc -l
8,701

TOP 10 QUALIFIERS (All)

(base) root@vm096:/app/kgtk/temp# kgtk sort -i /app/kgtk/data/my-tsv/quals-counted.tsv -c node2 --reverse-columns node2 --numeric-columns node2 / head
node1   label   node2
P1227   count   33122324
P972    count   23776643
P585    count   10432968
P642    count   8966228
P459    count   7930570
P580    count   7048511
P703    count   4317830
P582    count   3601028
P1545   count   3597770
P1057   count   2776317

TOP 10 QUALIFIERS (potencialmente controversos)

(base) root@vm096:/app/kgtk/temp# kgtk sort -i /app/kgtk/data/my-tsv/filtered-quals-counted.tsv -c node2 --reverse-columns node2 --numeric-columns node2 / head
node1   label   node2
P1227   count   32818028
P972    count   22180541
P642    count   8480507
P585    count   7860132
P459    count   5364796
P703    count   4304082
P580    count   3331943
P582    count   2525992
P1545   count   2474157
P1013   count   813579

# and % and distribution of % of controversial statements without qualifiers (contextually incomplete)

132,552,453 potencialmente controversos
2,599,600 potencialmente controversos por incompletude

1,96 %

Comando

(base) root@vm096:/home/cloud-di# more /app/kgtk/data/my-tsv/filtered-claims-sorted-uniq.tsv.gz | wc -l
132,552,454

(base) root@vm096:/app/kgtk/temp# more /app/kgtk/data/my-tsv/filtered-claims-without-quals-sorted.tsv.gz | wc -l
2,599,601

Comentários

Postagens mais visitadas deste blog

Connected Papers: Uma abordagem alternativa para revisão da literatura

Durante um projeto de pesquisa podemos encontrar um artigo que nos identificamos em termos de problema de pesquisa e também de solução. Então surge a vontade de saber como essa área de pesquisa se desenvolveu até chegar a esse ponto ou quais desdobramentos ocorreram a partir dessa solução proposta para identificar o estado da arte nesse tema. Podemos seguir duas abordagens:  realizar uma revisão sistemática usando palavras chaves que melhor caracterizam o tema em bibliotecas digitais de referência para encontrar artigos relacionados ou realizar snowballing ancorado nesse artigo que identificamos previamente, explorando os artigos citados (backward) ou os artigos que o citam (forward)  Mas a ferramenta Connected Papers propõe uma abordagem alternativa para essa busca. O problema inicial é dado um artigo de interesse, precisamos encontrar outros artigos relacionados de "certa forma". Find different methods and approaches to the same subject Track down the state of the art rese...

Knowledge Graph Embedding with Triple Context - Leitura de Abstract

  Jun Shi, Huan Gao, Guilin Qi, and Zhangquan Zhou. 2017. Knowledge Graph Embedding with Triple Context. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM '17). Association for Computing Machinery, New York, NY, USA, 2299–2302. https://doi.org/10.1145/3132847.3133119 ABSTRACT Knowledge graph embedding, which aims to represent entities and relations in vector spaces, has shown outstanding performance on a few knowledge graph completion tasks. Most existing methods are based on the assumption that a knowledge graph is a set of separate triples, ignoring rich graph features, i.e., structural information in the graph. In this paper, we take advantages of structures in knowledge graphs, especially local structures around a triple, which we refer to as triple context. We then propose a Triple-Context-based knowledge Embedding model (TCE). For each triple, two kinds of structure information are considered as its context in the graph; one is the out...

KnOD 2021

Beyond Facts: Online Discourse and Knowledge Graphs A preface to the proceedings of the 1st International Workshop on Knowledge Graphs for Online Discourse Analysis (KnOD 2021, co-located with TheWebConf’21) https://ceur-ws.org/Vol-2877/preface.pdf https://knod2021.wordpress.com/   ABSTRACT Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts . This data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting. While knowledge graphs promise to provide the key to a Web of structured information, they are mainly focused on facts without keeping track of the diversity, connection or temporal evolution of online discourse data. As opposed to facts, claims are inherently more complex. Their interpretation strongly depends on the context and a vari...