# From Discourse Relations to Network Edges: A Network Theory Approach to Discourse Analysis
## 6 Discussion  
We applied network analysis to two discourse-annotated corpora, STAC and C58, to uncover deep properties of discourse representations. The corpora contain English and Greek texts from two discourse types: multiparty dialogues and single-author written texts. We also analyzed the chat-only and situated versions of the multiparty dialogues in STAC. This helps us understand and compare how discourse structure varies across discourse types and languages. Initially, we presented key network indices for all discourse networks. C58 has a higher \(f_{e}\) compared with both STAC versions, though not significantly high. \(f_{e}\) represents network connectivity. The networks differ in size, measured by number of nodes (_resize_) and edges (_ledge_), but all are sufficiently large for reliable analyses. Despite being sparse, C58's discourse network exhibits a significantly higher mean fraction of edges than the STAC networks, indicating greater connectivity in single-author written texts, as expected. Furthermore, the clustering coefficients of C58 networks are noteworthy, comparable to those found in social networks (see Figure 10 and Table A1). However, they exhibit a tendency towards disassortativity, a characteristic commonly observed in technological or biological networks but rarely seen in social networks. Our study revealed remarkable differences and similarities between two discourse types: single-author written texts and dialogue texts in their chat-only and situated versions. Specifically, we examined the presence of network motifs and antimotifs:  
1. The linear chain pattern (\(S1\)) is not frequently observed as a motif in C58, despite the expectation that journalistic discourse would involve uninterrupted related se  
Figure 15: STAC (situated) networks—histograms of network motif z-scores. Three-node subgraph patterns are denoted as follows: \(S1\)—linear chain, \(S2\)—the feed-forward loop, \(S3\)—a cycle, \(S4\)—dual-cause and \(S5\)—common-cause. quences. In contrast, both versions of STAC systematically avoided the \(S1\) subgraph pattern, as evidenced by the absence of occurrences (see Table 11). These findings suggest that multiparty dialogue networks tend to avoid three uninterrupted related utterances, indicating that speakers do not participate in or contribute to a continuous line or chain of utterances. In C58, authors neither avoid nor prefer to establish connections between utterances in the form of a linear chain pattern. 2. The feed-forward pattern (\(S2\)) emerges as a motif in C58, indicating a statistically significant preference for constructing fully connected three-node subgraphs in most single-author written texts. This finding highlights the strong preference for fully connected three-node subgraphs in the discourse structures of single-author written texts. On the other hand, the two STAC discourse networks do not exhibit a network motif or antimotif, although it should be noted that no occurrences of the \(S2\) subgraph pattern were recorded in these networks. 3. Among all three discourse networks, the dual-cause pattern (\(S4\)) stands out as the only subgraph pattern that acts as an antimotif. In the three-node subgraphs of \(S4\), there is a node \(\pi_{3}\) with two incoming edges originating from two utterance labels, \(\pi_{1}\) and \(\pi_{2}\), which are not directly related to each other but precede in the discourse. 4. The common-cause pattern (\(S5\)) serves as an antimotif for the STAC corpora, while it does not exhibit characteristics of either a motif or an antimotif in the C58 corpus. This suggests that a commonly observed discourse strategy does not favor the scattered presentation of various aspects of an event described by an utterance. More typically, we witness a sequence of utterances that play a subordinate role to an initial utterance. It is generally avoided to circle back later in the discourse to add more aspects to that initial utterance.