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Datasets:
Cofacts
/
line-msg-fact-check-tw

Tasks:
Text Classification
Question Answering
Modalities:
Tabular
Text
Formats:
csv
Languages:
Chinese
Size:
10M - 100M
Tags:
fact-checking
crowd-sourcing
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
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metadata
license: cc-by-sa-4.0
language:
  - zh
pretty_name: Cofacts archive for reported messages and crowd-sourced fact-check replies
tags:
  - fact-checking
  - crowd-sourcing
size_categories:
  - 100K<n<1M
extra_gated_prompt: >-
  To access this repository, you agree to follow the [Cofacts Data User
  Agreement](https://github.com/cofacts/opendata/blob/master/LEGAL.md). This is
  vital to sustain a crowd-sourced database like Cofacts to attribute the
  fact-checking community that contributed to this dataset.

  欲存取此資料集，需同意[Cofacts 真的假的
  資料使用者條款](https://github.com/cofacts/opendata/blob/master/LEGAL.md)。
  彰顯查核社群對此資料集之貢獻，對協作型資料庫如 Cofacts 的永續發展至關重要。

  It would be great if you share with us who you are and your planned usage of
  the Cofacts data. Your cooperation is greatly appreciated. If you have no
  specific details to share with us, please simply enter "n/a."

  若方便的話，希望您可以與 Cofacts 工作小組分享您的單位以及預計會怎麼運用這個資料，感謝您！若不方便，可輸入「n/a」。
extra_gated_fields:
  I agree to follow the Data User Agreement and promise to attribute Cofacts as specified 我同意遵守資料使用者條款並承諾按規定彰顯 Cofacts: checkbox
  Anything to share with us 有什麼想要與我們分享的嗎: text
configs:
  - config_name: analytics
    data_files: analytics.csv.zip
  - config_name: article_categories
    data_files: article_categories.csv.zip
  - config_name: article_hyperlinks
    data_files: article_hyperlinks.csv.zip
    lineterminator: |+

  - config_name: article_replies
    data_files: article_replies.csv.zip
  - config_name: article_reply_feedbacks
    data_files: article_reply_feedbacks.csv.zip
    lineterminator: |+

  - config_name: articles
    data_files: articles.csv.zip
    lineterminator: |+

    default: true
  - config_name: categories
    data_files: categories.csv.zip
    lineterminator: |+

  - config_name: replies
    data_files: replies.csv.zip
    lineterminator: |+

  - config_name: reply_hyperlinks
    data_files: reply_hyperlinks.csv.zip
    lineterminator: |+

  - config_name: reply_requests
    data_files: reply_requests.csv.zip
    lineterminator: |+

  - config_name: anonymized_users
    data_files: anonymized_users.csv.zip
    lineterminator: |+

task_categories:
  - text-classification
  - question-answering

Cofacts Archive for Reported Messages and Crowd-Sourced Fact-Check Replies

Open In Colab

The Cofacts dataset encompasses instant messages that have been reported by users of the Cofacts chatbot and the replies provided by the Cofacts crowd-sourced fact-checking community.

Attribution to the Community

This dataset is a result of contributions from both Cofacts LINE chatbot users and the community fact checkers. To appropriately attribute their efforts, please adhere to the rules outlined in the Cofacts 真的假的 資料使用者條款 (Cofacts Data User Agreement).

Unless stated otherwise, when redistributing Cofacts data outside the LINE application, the attribution specified by the Cofacts Working Group is as follows:

This data by Cofacts message reporting chatbot and crowd-sourced fact-checking community is licensed under CC BY-SA 4.0. To provide more info, please visit Cofacts LINE bot https://line.me/ti/p/@cofacts

除非以其他方式議定，否則 Cofacts 真的假的工作小組，針對在 LINE 之外的地方散布的 Cofacts 所提供資料，所指定的中文顯名聲明為：

本編輯資料取自「Cofacts 真的假的」訊息回報機器人與查證協作社群，採 CC BY-SA 4.0 授權提供。若欲補充資訊請訪問 Cofacts LINE bot https://line.me/ti/p/@cofacts

For more detailed information, please refer to Cofacts 真的假的 資料使用者條款.

How to Access Cofacts Data

To access Cofacts data, you should first register on Hugging Face and accept the Cofacts Data User Agreement. Afterward, you can preview the data on the Hugging Face website.

You can access Cofacts data through the following methods:

  1. Load cofacts/line-msg-fact-check-tw with Hugging Face's load_dataset('Cofacts/line-msg-fact-check-tw', TABLE_NAME).
  2. Download individual zipped CSV files in the Files tab on the Hugging Face website.

If you plan to process the data using Python, load_dataset() is the simpler solution. Please refer to Example on Google Colab to get started.

Data Formats

Cofacts data comprises multiple normalized tables, with some tables containing foreign keys to other tables' IDs.

If you have manually downloaded the data, the tables are distributed as zipped CSV files. These files use \n as the line terminator, and quotes are used around multi-line contents. The csv-stringify library is employed to perform escaping and handle quotes and multi-line contents.

Fields in All Tables

  • userIdsha or userIdsha256 (string) Hashed user identifier.
  • appId (string) Possible values include:
    • LEGACY_APP: Articles collected before 2017-03.
    • RUMORS_LINE_BOT: Articles collected with the current LINE bot client after 2017-03.

These two fields together uniquely identify a user across different CSV files. For example, if one row (reply) in replies.csv and another row (feedback) in article_reply_feedbacks.csv have identical userIdsha and appId, it indicates that the reply and the feedback were submitted by the same user.

Also, these fields are commonly seen in multiple tables:

  • status: The current visibility of this document. Possible values include:
    • NORMAL: The document is normally visible.
    • DELETED: The document is deleted by its author. For some entities (tables), deletion is not implemented, and thus does not have such value.
    • BLOCKED: The document is hidden by Cofacts Working Group. These document are from a blocked user, with blockedReason pointing to announcements in Cofacts Takedown Announcements.

Tables and their fields

articles

The instant messages LINE bot users submitted into the database.

Field Data type Description
id String
articleType Enum string TEXT, IMAGE, VIDEO or AUDIO.
status Enum string NORMAL or BLOCKED.
text Text The instant message text
normalArticleReplyCount Integer The number of replies are associated to this article, excluding the deleted reply associations.
createdAt ISO time string When the article is submitted to the database.
updatedAt ISO time string Preserved, currently identical to createdAt
lastRequestedAt ISO time string The submission time of the last reply_request is sent on the article, before the article is replied.
userIdsha256 String Author of the article.
appId String
references Enum string Where the message is from. Currently the only possible value is LINE.

article_hyperlinks

Parsed hyperlink contents in each instant messages, parsed using cofacts/url-resolver. The data is used in Cofacts system for indexing and retrieving messages.

Field Data type Description
articleId String
url String The URL string detected in article
normalizedUrl String Canonical URL after normalization process including unfolding shortened URLs
title String Title of the scrapped web content

Note: Scrapped contents do not belong to Cofacts and are redistributed under research purposes. The scrapping mechanism is not reliable either. Researchers may need to implement their own scrapper if content is important in their research.

article_categories

Categories linked to this article.

Field Data type Description
articleId String
categoryId String
aiConfidence Number Confidence level by AI marking this category. Empty for crowd-sourced labels.
aiModel . String Name of the AI model marking this cateogry. Empty for crowd-sourced labels.
userIdsha String The person that connected article and category.
appId . String
negativeFeedbackCount Integer Number of article_category_feedbacks that has score -1
positiveFeedbackCount Integer Number of article_category_feedbacks that has score 1
status Enum string NORMAL: The category and article are connected. DELETED: The category does not connect to the article anymore.
createdAt ISO time string The time when the reply is connected to the article
updatedAt ISO time string The latest date when the category's status is updated

categories

Field Data type Description
id String
title String Name of the category
description Text Definition of the category
createdAt ISO time string
updatedAt ISO time string

article_replies

Articles and replies are in has-and-belongs-to-many relationship. That is, an article can have multiple replies, and a reply can be connected to multiple similar articles.

article_replies is the "join table" between articles and replies, bringing articleId and replyId together, along with other useful properties related to this connection between an article and a reply.

One pair of articleId, replyId will map to exactly one article_reply.

Field Data type Description
articleId String Relates to id field of articles
replyId String Relates to id field of replies
userIdsha256 String The user connecting the reply with the article
negativeFeedbackCount Integer Number of article_reply_feedbacks that has score -1
positiveFeedbackCount Integer Number of article_reply_feedbacks that has score 1
replyType Enum string Duplicated from replies's type.
appId String
status Enum string NORMAL: The reply and article are connected. DELETED: The reply does not connect to the article anymore. BLOCKED: It comes from a blocked user.
createdAt ISO time string The time when the reply is connected to the article
updatedAt ISO time string The latest date when the reply's status is updated

replies

Editor's reply to the article.

Field Data type Description
id String
type Enum string Type of the reply chosen by the editor. RUMOR: The article contains rumor. NOT_RUMOR: The article contains fact. OPINIONATED: The article contains personal opinions. NOT_ARTICLE: The article should not be processed by Cofacts.
reference Text For RUMOR and NOT_RUMOR replies: The reference to support the chosen type and text. For OPINIONATED replies: References containing different perspectives from the article. For NOT_ARTICLE: empty string.
userIdsha256 String The editor that authored this reply.
appId String
text Text Reply text writtern by the editor
createdAt ISO Time string When the reply is written

reply_hyperlinks

Parsed hyperlink contents in reply text and references, parsed using cofacts/url-resolver. The data is used in Cofacts system for URL previews.

Field Data type Description
replyId String
url String The URL string detected in article
normalizedUrl String Canonical URL after normalization process including unfolding shortened URLs
title String Title of the scrapped web content

Note: Scrapped contents do not belong to Cofacts and are redistributed under research purposes. The scrapping mechanism implementation is not reliable either. Researchers may need to implement their own scrapper if content is important in their research.

reply_requests

Before an article is replied, users may submit reply_requests to indicate that they want this article to be answered.

When an article is first submitted to the article, an reply request is also created. Any further queries to the same article submits new reply_requests.

An user can only submit one reply request to an article.

Field Data type Description
articleId String The target of the request
reason Text The reason why the user wants to submit this reply request
status Enum string NORMAL or BLOCKED.
positiveFeedbackCount Text Number of editors think the reason is reasonable
negativeFeedbackCount Text Number of editors think the reason is nonsense
userIdsha256 String The user that submits this reply request
appId String
createdAt ISO Time string When the reply request is issued

article_reply_feedbacks

Editors and LINE bot users can express if a reply is useful by submitting article_reply_feedbacks toward a article_reply with score 1 or -1.

The feedback is actually submitted toward an article_reply, the connection between an article and a reply. This is because a reply can be connected to multiple articles. A reply that makes sense in one article does not necessarily mean that it is useful in answering another article. Therefore, the feedback count for a reply connecting to different articles are counted separately.

Field Data type Description
articleId String Relates to articleId of the target article_reply
replyId String Relates to replyId of the target article_reply
score Integer 1: Useful. -1: Not useful.
comment Text Why the user chooses such score for this article reply
status Enum string NORMAL or BLOCKED.
userIdsha256 String The user that submits this feedback.
appId String
createdAt ISO Time string When the feedback is submitted

analytics

Usage (visit / show) statistics of website and Cofacts LINE bot.

LINE bot data starts from April 2nd, 2018; website data starts from May 3rd, 2017.

Field Data type Description
type Enum string Either article or reply
docId String Article ID or Reply ID that is being visited / shown
date ISO Time string The date of usage, represented by start of the day (0:00:00+08:00)
lineUser Integer The number of LINE users who inspected this article / reply in Cofacts LINE bot in this date. May be empty if no such users
lineVisit Integer The number of times this article / reply is inspected in Cofacts LINE bot in this date. May be empty if no visits
webUser Integer The number of web users who visited this article page (/article/<docId>) / reply page (/reply/<docId>) in Cofacts website in this date. May be empty if no such users
webVisit Integer The number of page views of this article page (/article/<docId>) / reply page (/reply/<docId>) in Cofacts website in this date. May be empty if no page views

anonymized_usrs

The users of Cofacts, including Cofacts chatbot and website users.

Field Data type Description
userIdsha256 String The ID that is used in other tables to denote the creator of the entity.
appId String Where this user account is registered. RUMORS_LINE_BOT is Cofacts official LINE account. Registered user on Cofacts website has empty appId.
createdAt ISO Time string The initial registration date for the user.
lastActiveAt ISO Time string The last date the account is active.
blockedReason String If exists, all submission from the user is hidden by Cofacts WG. This field contains the announcement to the reason why Cofacts WG blocks such user.

⚠ [NOTICE] Caveats of using this data ⚠

The methodology we use to collect these data (i.e. how Cofacts works) could have some impact on the data credibility.

How cofacts work

Please keep in mind that all data in this dataset are user-generated, thus is not free from noise and sampling bias coming from these sources:

  • The distribution Cofacts' users may not reflect the real distribution of all LINE users in Taiwan.
  • Users may not use Cofacts in the same way we want them to be. Some articles may not be actual messages circulating in LINE network.
  • replies may contain factual error. All replies should be merely regarded as "responses to the original message (article) to provide different point of view". They are neither the "truth" nor the editor's personal opinion.
  • There may also exist malicious users sending garbage articles into the database. (Previous incident reports)
  • The program to collect data and to generate dataset may contain error. The dataset may be inaccurate systematically in this way.

Lastly, the dataset is provided without warrenty.

THE DATASET IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATASET OR THE USE OR OTHER DEALINGS IN THE DATASET.