3. Argument mapping vs. mind mapping

It is frequently asked how Argunet differs from mind mapping software. Why should one choose to use Argunet when there are already various mind mapping alternatives available?

Argument mapping software is not better than mind mapping software in general. Depending on the context of application, an argument mapping or a mind mapping software may be more suitable.

A mind map is the visualization of connections between thoughts and ideas in a map-like structure. Any type of thought fragment or association can be organized and brought into a suitable mnemonic form. At first glance, the corresponding maps may resemble the argument maps constructed with Argunet. There are, however, substantial differences concerning the method and aim of the two approaches.

An argument map, on the other hand, represents reasons for and against one (or more) controversial theses. It can be used to reconstruct argumentations logically using approaches from argumentation theory, to analyse and to evaluate them. Thus, the aim is more specific and narrow, and the method is more rigorous and sophisticated.

The following table gives an overview of the properties of mind mapping software and points out the differences in method which make this software unsuitable for argument mapping.

Table 1.1.  Why Argunet is more suitable for argument mapping than mind mapping software

AspectMind mapping softwareArgument mapping with argunet
Purpose Mind mapping: brainstorming, note taking, categorization of any type of content Argument mapping: reconstruction and categorization of complex argumentations and controversial debates
Creative freedom vs intelligibility The more creative freedom the user has, the better! Images, colours, and shapes should be available to the user. Keep it simple! When creating and reading an argument map, the user should be able to concentrate on the content without having to pay attention to the graphical representation. The meaning of the graphical elements is fixed to guarantee general intelligibility.
Variety of appications vs functional specialization The more fields of application, the better! If a tool's field of application (the logical reconstruction of debates) is restricted, it will fulfil its function better.
Brainstorming vs logical analysis and reconstruction Brainstorming software must allow users to jot down vague associations as easily, quickly and unrestrictedly as possible. Software for logical reconstruction must allow users to analyze reasons in a precise, detailed, consistent and rule-guided manner.
Nodes: content The user can fill nodes with any type of content (for example "Berlin", "flour", "democracy", "ozon hole", "mayor"). The structure of the content is not predefined. Argument maps contain only arguments and sentences. Arguments consist of a premiss-conclusion-structure, a short description, a title, an inference pattern (optional), a formalization (optional), references (optional), comments (optional), etc.
Nodes: design The user can customize the design of the nodes. The visualization of arguments and sentences using colour coding, shape, etc. is predefined in order to represent argumentation-theoretic properties of the nodes intelligibly and consistently.
Nodes: content The user can create any type of relation (for example "...requires...", "...is father of...", "...prevents...", "...consists of...", "...negates..."). These relations are not clearly defined and cannot be inserted automatically. There are only two relations between nodes, attack and support. These relations are defined logically and are based on sentence equivalence classes and contrary relations between them. Thus, consistency management for the logical relations can be performed automatically, and new relations are inserted automatically when new sentences and arguments are added to the argument map.
Edges: design The user can customize any edge. Attack and support relations are colour coded intuitively (red and green). Furthermore, sketched and logically reconstructed relations are distinguished graphically.
Structure of the graph Mind maps are usually planar and constructed hierarchically (tree structure). Argument maps can exhibit circular structures, they can be multipolar, and they can contain many crosslinks and overlaps.
Contradicting positions Mind maps are not suitable for the representation of contradicting positions. These are difficult to represent and require a very skilled user. Argument maps were designed to represent contradicting positions. The participants in a debate can be visualized using systematic colour coding, and the contradictions become apparent in the logical relations.
Consistency and coherence Because of their lack of structure and their openness, mind maps cannot be used to check or guarantee the consistency and coherence of a position. With their rule-guided structure, argument maps quickly reveal the contradictions and connections between positions.
Collaboration Mind maps are hardly suitable for collaboration of medium-sized and larger groups. A high degree of coordination is required, and consensus is a prerequisite. Because of their unambiguous visualization and the rigorous definition of their content, argument maps are especially suitable for structuring controversial debates. Collaboration in medium-sized and large groups is facilitated by the rule-guided editing of arguments. Consensus is not a prerequisite (diversity of opinion is the typical case).
Presentation, intelligibility, objectivity Mind maps are not necessarily intelligible to other users, as a) their main aim is often precisely to record subjective, individual associations and categorizations in preparation for further enquiry, and b) the visualization is not rule-guided and standardized for all argument maps. Argument map are intelligible to other users, as a) they reconstruct the logical and semantic relations of our utterances that hold intersubjectively, and b) their visualization is rule-guided and standardized for all argument maps.
Evaluation As neither nodes nor edges are defined exactly, automatic evaluation is practically impossible. Exact definition of nodes and edges allows for various methods of automatic evaluation.