Argumentation dataset with individual attitudes

Definitions

Following the IBIS model, we have

• 2 positions:
  • Should plastic packaging for fresh food such as fruit and vegetables be allowed (0) or prohibited (1) in Germany? (id 363)
  • Should the growing of genetically modified plants for food production be allowed (0) or prohibited (1) in Germany? (id 324)
• arguments for/against each position

Each participant indicated

• their opinion on the positions (0/1)
• whether they consider an argument convincing (1) or not (0)
• their opinion strength (0-6)

Overview

A certain set of arguments have been provided by us before, more arguments have been added by participants.

• plastic packaging: 36+521 arguments
• genetic engineering: 38+351 arguments

Data collection

The data has been collected at four different points of time, where different participants provided their attitudes on positions and arguments formulated by us:

• T0: Pre-test data with 264 participants; opinions and opinion strengths on the positions plastic packaging and genetic engineering; opinions and convincingness on 14 randomly selected arguments per topic
• T1: first main experiment with 410 participants; opinions and opinion strengths on plastic packaging and genetic engineering
• T2: second main experiment with 289 participants (subset of users from T1); opinions and opinion strengths on plastic packaging and genetic engineering; opinions and convincingness on 6 randomly selected argument for/against plastic packing (3 randomly selected supporting, and 3 randomly selecting attacking arguments); users were able to contribute own arguments on the topic plastic packaging (relevant statement ids: 364-399)
• T3: third main experiment with 229 participants (subset of users from T2); opinions and opinion strengths on plastic packaging and genetic engineering; opinions and convincingness on 6 randomly selected argument for/against genetic engineering (3 randomly selected supporting, and 3 randomly selecting attacking arguments); users were able to contribute own arguments on the topic genetic engineering (relevant statement ids: 325-362)

For details on the data collection and the context of the original experiment (which included more groups and users, where the presentation of arguments was different), see .

Provided files

We provide the following files:

• arguments.csv: all statements and positions, as provided by us or contributed by the participants:
  • statement_id: ID of the statement
  • conclusions: list of statement sid which were used as conclusion for this statement (empty for positions) and the information whether the formed argument is supportive (+) or attacking (-)
  • text: original (German) text of this statement
  • text_en: English translation of the text
  • author: the author of the argument, either UPEKI (we), or a user name
• arguments.json: all arguments in the Argument Interchange Format (AIF)
• train.csv
  • for each user, contains the agreement(1)/disagreement(0) attitude information for positions/arguments, as well as strength ratings
  • rating_after is the value for a position provided at that point of time (T1 or T2)
  • rating_before is the value for a position provided at the previoud point of time (T2 or T3)
  • folder T1_T2: data contains information after T1, before T2
    • i.e. complete data for pre-test participants, only opinion on positions for main experiment participants
  • folder T2_T3: data contains information after T2, before T3
    • i.e. complete data for pre-test participants, argument attitudes for plastic packaging for main experiment participants
• validation.csv
  • same structure as train.csv
  • folder T1_T2: data contains information after T2, before T3
    • i.e. argument attitudes for plastic packaging for half of the main experiment participants
  • folder T1_T3: data contains information after T3
    • i.e. complete data for half of the main experiment participants
• test.csv
  • same as validation.csv, but for the other half of main experiment participants
• T0.csv, T1.csv, T2.csv, T3.csv in complete:
  • same structure as train.csv for the individual T1→T2/T2→T3 sets
  • contains the complete data from the points of time, without any split

Relevant publications

Markus Brenneis, Maike Behrendt, and Stefan Harmeling (July 2021). “How Will I Argue? A Dataset for Evaluating Recommender Systems for Argumentations”. In: Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue. Singapore and Online: Association for Computational Linguistics, pp. 360–367