Annotating Shallow Discourse Relations in Twitter Conversations

Scheffler, Tatjana; Aktaş, Berfin; Das, Debopam; Stede, Manfred

doi:10.18653/v1/w19-2707

Cited by 7 publications

(6 citation statements)

References 6 publications

(6 reference statements)

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“…Media differences in the use of (causal) conjunctions have for example been documented in persuasive news texts and Twitter posts (Scheffler & Stede 2016), but without reference to other registers.…”

Section: Discussionmentioning

confidence: 99%

The medium is not the message

Scheffler

Kern

Seemann

2022

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Linguistic expressions in social media vary along many axes, including author style, the specific medium and its affordances, and others. In this paper, we argue that different registers must be distinguished within social media and that register should be included as an important factor independent of (social) medium in analyses of variable linguistic phenomena. We introduce a new German cross-media corpus, consisting of blog posts and tweets from the same 44 authors. We define the registers as ‘Informative’, ‘Narrative’, and ‘Persuasive’, based on situational characteristics of the texts. We then correlate the registers with two variable linguistic phenomena: German modal and intensifying particles. In each case, we document considerable inter- and intraindividual variation in the expressions used and their frequency across texts. The statistical analysis shows that the register grouping corresponds more closely to linguistic similarities between texts than the grouping by medium does.

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Section: Discussionmentioning

confidence: 99%

The medium is not the message

Scheffler

Kern

Seemann

2022

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“…Zeyrek et al (2018) annotate 6 TED talks for 7 languages. Scheffler et al (2019) build a discourse corpus on Twitter Conversations. Regarding Chinese discourse corpora for discourse relations, as illustrated in Table 1, there are mainly 4 Chinese discourse corpora based on the PDTB framework (Prasad et al, 2008a).…”

Section: Related Workmentioning

confidence: 99%

TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks

Long¹,

Webber

Xiong

2020

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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As different genres are known to differ in their communicative properties and as previously, for Chinese, discourse relations have only been annotated over news text, we have created the TED-CDB dataset. TED-CDB comprises a large set of TED talks in Chinese that have been manually annotated according to the goals and principles of Penn Discourse Treebank, but adapted to features that are not present in English. It serves as a unique Chinese corpus of spoken discourse. Benchmark experiments show that TED-CDB poses a challenge for state-of-the-art discourse relation classifiers, whose F1 performance on 4way classification is <60%. This is a dramatic drop of 35% from performance on the news text in the Chinese Discourse Treebank. Transfer learning experiments have been carried out with the TED-CDB for both same-language cross-domain transfer and same-domain crosslanguage transfer. Both demonstrate that the TED-CDB can improve the performance of systems being developed for languages other than Chinese and would be helpful for insufficient or unbalanced data in other corpora. The dataset and our Chinese annotation guidelines has been made freely available. 1

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“…There is a claim in the literature that microblogs and blogs are similar to spoken conversations (e.g. [Scheffler et al 2019], [Akhapkina 2014] etc.). According to [Chafe 1982] (see also [Kibrik, Podlesskaya eds.…”

Section: Difference In Register For Spoken and Written Discoursementioning

confidence: 99%

“…Many studies deal with the features that blogs share with spoken conversations ( [Simaki et al 2017: 14], [Scheffler et al 2019] etc.). Fragmented or incomplete clauses, dialogic interaction expressions are among them.…”

Section: Spoken Discourse Features In Blogsmentioning

confidence: 99%

Discourse Features of Blogs in Subcorpus of Russian Ru-Rstreebank

Toldova¹,

Davydova²,

Kobozeva³

et al. 2020

Computational Linguistics and Intellectual Technologies

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The paper presents a corpus study of the discourse features in the corpus of blogs. It is based on the data of Ru-RSTreebank annotated within the framework of the Rhetorical Structure theory [Mann, Thompson 1988]. The Ru-RSTreebank represents genres of news and popular science, scientific papers, and blogs texts. Blog subcorpus contains such topics as travelling, cosmetics, sports and health, psychology, IT and tech and some others. Blogs texts constitute a specific genre as they combine properties of written and spoken discourse. The purpose of the paper is to investigate discourse features of blogs in comparison with other genres. We analyze the variation in rhetoric relations distribution among genres, and single out the differences in discourse connectives usage. Furthermore, we check the distribution of other discourse features reported in different studies for spoken discourse and for social media in the Ru-RSTreebank blogs subcorpus. The general frequency analysis and the experiments on RandomForest classifier application to genre recognition have shown that the most important rhetoric relations specific to blogs are Evaluation and Contrast, that there is a tendency to use shorter discourse units and not to express the discourse relations overtly via subordinative conjunctions.

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Annotating Shallow Discourse Relations in Twitter Conversations

Cited by 7 publications

References 6 publications

The medium is not the message

The medium is not the message

TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks

Discourse Features of Blogs in Subcorpus of Russian Ru-Rstreebank

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