Involvement drives complexity of language in online debates | Paper Citation Record

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This paper cites The Cambridge encyclopedia of the English language.

Involvement drives complexity of language in online debates The Cambridge encyclopedia of the English language

Reference 1

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This paper cites Language contact, creolization, and genetic linguistics.

Involvement drives complexity of language in online debates Language contact, creolization, and genetic linguistics

Reference 2

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This paper cites Mediatization and sociolinguistic change, volume 36.

Involvement drives complexity of language in online debates Mediatization and sociolinguistic change, volume 36

Reference 3

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This paper cites Evaluating the effect of viral posts on social media engagement.

Involvement drives complexity of language in online debates Evaluating the effect of viral posts on social media engagement

Reference 4

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Observation fcf8749a-5c6c-4c2d-91c4-6ef3557c4383 · outbound

This paper cites Filter bubbles, echo chambers, and online news consumption.

Involvement drives complexity of language in online debates Filter bubbles, echo chambers, and online news consumption

Reference 5

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This paper cites The echo chamber effect on social media.

Involvement drives complexity of language in online debates The echo chamber effect on social media

Reference 6

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This paper cites Like-minded sources on facebook are prevalent but not polarizing.

Involvement drives complexity of language in online debates Like-minded sources on facebook are prevalent but not polarizing

Reference 7

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This paper cites Social media, political polarization, and political disinformation: A review of the scientific literature.

Involvement drives complexity of language in online debates Social media, political polarization, and political disinformation: A review of the scientific literature

Reference 8

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Observation d10dce2e-c298-49e4-a2bb-fb5dbb98a696 · outbound

This paper cites Growing polarization around climate change on social media.

Involvement drives complexity of language in online debates Growing polarization around climate change on social media

Reference 9

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This paper cites Se l’uomo non basta: Speranze e timori nell’uso della tecnologia contro Covid-19.

Involvement drives complexity of language in online debates Se l’uomo non basta: Speranze e timori nell’uso della tecnologia contro Covid-19

Reference 10

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This paper cites Eugene Stanley, and Walter Quattrociocchi.

Involvement drives complexity of language in online debates Eugene Stanley, and Walter Quattrociocchi

Reference 11

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Involvement drives complexity of language in online debates Unresolved cited work

Reference 12

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Observation 16ed21f9-127b-4ec2-8a49-f29ed5428e67 · outbound

This paper cites Internet, social media and online hate speech.

Involvement drives complexity of language in online debates Internet, social media and online hate speech

Reference 13

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Observation 9298dc6f-ed81-4a6d-a268-149b4e57e3ef · outbound

This paper cites Online hate speech.

Involvement drives complexity of language in online debates Online hate speech

Reference 14

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This paper cites A large-scale behavioural analysis of bots and humans on twitter.

Involvement drives complexity of language in online debates A large-scale behavioural analysis of bots and humans on twitter

Reference 15

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This paper cites Persistent interaction patterns across social media platforms and over time.

Involvement drives complexity of language in online debates Persistent interaction patterns across social media platforms and over time

Reference 16

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Observation dda595a4-7794-4a14-ab35-4ce7538e5475 · outbound

This paper cites Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platforms.

Involvement drives complexity of language in online debates Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platforms

Reference 17

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This paper cites Sentiment analysis with nlp on twitter data.

Involvement drives complexity of language in online debates Sentiment analysis with nlp on twitter data

Reference 18

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Observation 2bc49725-5ec9-46f2-a211-06bd7f06f3c7 · outbound

This paper cites Covid-twitter-bert: A natural language processing model to analyse covid-19 content on twitter.

Involvement drives complexity of language in online debates Covid-twitter-bert: A natural language processing model to analyse covid-19 content on twitter

Reference 19

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Observation cb089dae-12f3-451c-97cf-e0c012f117f2 · outbound

This paper cites Inference of social media opinion trends in 2022 italian elections.

Involvement drives complexity of language in online debates Inference of social media opinion trends in 2022 italian elections

Reference 20

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This paper cites Using the president’s tweets to understand political diversion in the age of social media.

Involvement drives complexity of language in online debates Using the president’s tweets to understand political diversion in the age of social media

Reference 21

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This paper cites Twitter as arena for the authentic outsider: exploring the social media campaigns of trump and clinton in the 2016 us presidential election.

Involvement drives complexity of language in online debates Twitter as arena for the authentic outsider: exploring the social media campaigns of trump and clinton in the 2016 us presidential election

Reference 22

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This paper cites Use of sentiment analysis for capturing patient experience from free-text comments posted online.

Involvement drives complexity of language in online debates Use of sentiment analysis for capturing patient experience from free-text comments posted online

Reference 23

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This paper cites Sentiment analysis of comment texts based on bilstm.

Involvement drives complexity of language in online debates Sentiment analysis of comment texts based on bilstm

Reference 24

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Observation 5bae79ed-b21e-43a0-91be-0a4fedb72ef0 · outbound

This paper cites Sentiment analysis of comments in social media.

Involvement drives complexity of language in online debates Sentiment analysis of comments in social media

Reference 25

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This paper cites Inferring latent user properties from texts published in social media.

Involvement drives complexity of language in online debates Inferring latent user properties from texts published in social media

Reference 26

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This paper cites Evolution of the most common english words and phrases over the centuries.

Involvement drives complexity of language in online debates Evolution of the most common english words and phrases over the centuries

Reference 27

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This paper cites Measurement of the size of general english vocabulary through the elementary grades and high school.

Involvement drives complexity of language in online debates Measurement of the size of general english vocabulary through the elementary grades and high school

Reference 28

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This paper cites Breadth of vocabulary and advanced english study: An empirical investigation.

Involvement drives complexity of language in online debates Breadth of vocabulary and advanced english study: An empirical investigation

Reference 29

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This paper cites V ocabulary size revisited: the link between vocabulary size and academic achievement.

Involvement drives complexity of language in online debates V ocabulary size revisited: the link between vocabulary size and academic achievement

Reference 30

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This paper cites Always on: Language in an online and mobile world.

Involvement drives complexity of language in online debates Always on: Language in an online and mobile world

Reference 31

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This paper cites Because internet: Understanding the new rules of language.

Involvement drives complexity of language in online debates Because internet: Understanding the new rules of language

Reference 32

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This paper cites Discourse of Twitter and social media.

Involvement drives complexity of language in online debates Discourse of Twitter and social media

Reference 33

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This paper cites Words onscreen: The fate of reading in a digital world.

Involvement drives complexity of language in online debates Words onscreen: The fate of reading in a digital world

Reference 34

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This paper cites Di Marco, Edoardo Loru, Anita Bonetti, Alessandra Olga Grazia Serra, Matteo Cinelli, and Walter Quattro- ciocchi.

Involvement drives complexity of language in online debates Di Marco, Edoardo Loru, Anita Bonetti, Alessandra Olga Grazia Serra, Matteo Cinelli, and Walter Quattro- ciocchi

Reference 35

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This paper cites Highly engaging events reveal semantic and temporal compression in online community discourse.

Involvement drives complexity of language in online debates Highly engaging events reveal semantic and temporal compression in online community discourse

Reference 36

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This paper cites Song lyrics have become simpler and more repetitive over the last five decades.

Involvement drives complexity of language in online debates Song lyrics have become simpler and more repetitive over the last five decades

Reference 37

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This paper cites Decoding Musical Evolution Through Network Science.

Involvement drives complexity of language in online debates Decoding Musical Evolution Through Network Science

Reference 38

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This paper cites Who sets the agenda on social media? ideology and polarization in online debates.

Involvement drives complexity of language in online debates Who sets the agenda on social media? ideology and polarization in online debates

Reference 39

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This paper cites Tweets in time of conflict: A public dataset tracking the twitter discourse on the war between Ukraine and Russia.

Involvement drives complexity of language in online debates Tweets in time of conflict: A public dataset tracking the twitter discourse on the war between Ukraine and Russia

Reference 40

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This paper cites quanteda: An r package for the quantitative analysis of textual data.

Involvement drives complexity of language in online debates quanteda: An r package for the quantitative analysis of textual data

Reference 41

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This paper cites Republicans are flagged more often than democrats for sharing misinformation on x’s community notes.

Involvement drives complexity of language in online debates Republicans are flagged more often than democrats for sharing misinformation on x’s community notes

Reference 42

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This paper cites Chatgpt outperforms crowd workers for text-annotation tasks.

Involvement drives complexity of language in online debates Chatgpt outperforms crowd workers for text-annotation tasks

Reference 43

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This paper cites Predicting the topical stance and political leaning of media using tweets.

Involvement drives complexity of language in online debates Predicting the topical stance and political leaning of media using tweets

Reference 44

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This paper cites Political polarization of news media and influencers on twitter in the 2016 and 2020 us presidential elections.

Involvement drives complexity of language in online debates Political polarization of news media and influencers on twitter in the 2016 and 2020 us presidential elections

Reference 45

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This paper cites TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification.

Involvement drives complexity of language in online debates TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification

Reference 46

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Involvement drives complexity of language in online debates RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 47

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This paper cites Xlm-roberta based sentiment analysis of tweets on metaverse and 6g.

Involvement drives complexity of language in online debates Xlm-roberta based sentiment analysis of tweets on metaverse and 6g

Reference 48

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This paper cites Sentiment analysis in tweets: an assessment study from classical to modern word representation models.

Involvement drives complexity of language in online debates Sentiment analysis in tweets: an assessment study from classical to modern word representation models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.701643Z

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This paper cites Analyzing sentiments: A comprehensive study of roberta-based sentiment analysis on twitters.

Involvement drives complexity of language in online debates Analyzing sentiments: A comprehensive study of roberta-based sentiment analysis on twitters

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.533595Z

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This paper cites Transformer models for recognizing abusive language an investigation and review on tweeteval and solid dataset.

Involvement drives complexity of language in online debates Transformer models for recognizing abusive language an investigation and review on tweeteval and solid dataset

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.371440Z

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This paper cites Roberta-lstm: a hybrid model for sentiment analysis with transformer and recurrent neural network.

Involvement drives complexity of language in online debates Roberta-lstm: a hybrid model for sentiment analysis with transformer and recurrent neural network

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.264088Z

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This paper cites BERTweet: A pre-trained language model for English Tweets.

Involvement drives complexity of language in online debates BERTweet: A pre-trained language model for English Tweets

Reference 53

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This paper cites TweetEval: Unified benchmark and comparative evaluation for tweet classification.

Involvement drives complexity of language in online debates TweetEval: Unified benchmark and comparative evaluation for tweet classification

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.178965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9a272e98-06d2-4f71-a5e5-868553167145 · outbound

This paper cites A machine learning approach to identify toxic language in the online space.

Involvement drives complexity of language in online debates A machine learning approach to identify toxic language in the online space

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:01.079739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20177a5e-0dce-42b0-a2f8-a8d547a57bf4 · outbound

This paper cites UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection.

Involvement drives complexity of language in online debates UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:15:57.574206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1ecae261-c9ef-4c42-9cb3-a1c3614b7961 · outbound

This paper cites TimeLMs: Diachronic language models from Twitter.

Involvement drives complexity of language in online debates TimeLMs: Diachronic language models from Twitter

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:00.958443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4b5479f8-24c7-4e3f-ad12-c8e1b24e0303 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Involvement drives complexity of language in online debates BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T22:15:55.967007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be3cf4aa-948d-4a3d-9bfc-3b71b50f92ea · outbound

This paper cites Density-based clustering validation.

Involvement drives complexity of language in online debates Density-based clustering validation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:00.711930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d290a086-6fc1-4368-a900-2ddae99f3e93 · outbound

This paper cites Indicators of text complexity.

Involvement drives complexity of language in online debates Indicators of text complexity

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:00.501154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 28270f23-6a99-4ef0-bb83-1a5f6bf86e36 · outbound

This paper cites The psycho-biology of language: An introduction to dynamic philology.

Involvement drives complexity of language in online debates The psycho-biology of language: An introduction to dynamic philology

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:16:00.260342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3dd3af5f-c535-4d0e-842e-0427f93c5266 · outbound

This paper cites Computational constancy measures of texts—yule’s k and rényi’s entropy.

Involvement drives complexity of language in online debates Computational constancy measures of texts—yule’s k and rényi’s entropy

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.989074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c466aa3-324d-4e3a-ac19-3d8621307900 · outbound

This paper cites On measures of entropy and information.

Involvement drives complexity of language in online debates On measures of entropy and information

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.829156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1007877f-f17b-4416-9ef9-1c5eb171a3cc · outbound

This paper cites Vocabulaire et stylistique, volume 8.

Involvement drives complexity of language in online debates Vocabulaire et stylistique, volume 8

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.613358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dd2a460e-5037-4df2-a0d2-a447db2c91be · outbound

This paper cites How variable may a constant be? measures of lexical richness in perspective.

Involvement drives complexity of language in online debates How variable may a constant be? measures of lexical richness in perspective

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.397971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 18e561ef-c791-4d7c-a276-05d3abec6fe5 · outbound

This paper cites The statistical study of literary vocabulary.

Involvement drives complexity of language in online debates The statistical study of literary vocabulary

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.244349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4aa97fa4-fbe0-41b3-a404-66fb829f7c85 · outbound

This paper cites Highly engaging events reveal semantic and temporal compression in online community discourse.

Involvement drives complexity of language in online debates Highly engaging events reveal semantic and temporal compression in online community discourse

Reference 67

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T22:15:57.348339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c79041fc-3077-4199-9968-e6f8d5833681 · outbound

This paper cites Trade liberalization and revealed comparative advantage.

Involvement drives complexity of language in online debates Trade liberalization and revealed comparative advantage

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:59.055211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 93287ef3-5be8-41c0-bee9-91301c479303 · outbound

This paper cites Inferring monopartite projections of bipartite networks: an entropy-based approach.

Involvement drives complexity of language in online debates Inferring monopartite projections of bipartite networks: an entropy-based approach

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.874932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2ceed552-1061-4a53-89df-cbe6176fc576 · outbound

This paper cites The statistical physics of real-world networks.

Involvement drives complexity of language in online debates The statistical physics of real-world networks

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.783292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5dc6fd60-59c5-4833-ac73-a1154853faa9 · outbound

This paper cites Controlling the false discovery rate: A practical and powerful approach to multiple testing.

Involvement drives complexity of language in online debates Controlling the false discovery rate: A practical and powerful approach to multiple testing

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.681198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08d69a5e-6ca4-4198-8729-d65c16f307ba · outbound

This paper cites Fast and scalable likelihood maximization for exponential random graph models with local constraints.

Involvement drives complexity of language in online debates Fast and scalable likelihood maximization for exponential random graph models with local constraints

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.489177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 19779d01-f198-462f-9257-f401b7da0473 · outbound

This paper cites Hagberg, Daniel A.

Involvement drives complexity of language in online debates Hagberg, Daniel A

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.358986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a6c91c7f-3812-4176-9a0b-51ffe0da52b6 · outbound

This paper cites Gephi: An open source software for exploring and manipulating networks.

Involvement drives complexity of language in online debates Gephi: An open source software for exploring and manipulating networks

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.258245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f95c6647-7c87-43ea-a4ec-94d90a0ce8e9 · outbound

This paper cites L” (Left), combining “left.

Involvement drives complexity of language in online debates L” (Left), combining “left

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:58.084457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a0086fd-4740-4fa7-b0ac-2c2b9271029e · outbound

This paper cites an unresolved cited work.

Involvement drives complexity of language in online debates Unresolved cited work

Reference 1995

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:15:58.604032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers