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Knowledge and Information Systems
Published in: Knowledge and Information Systems 9/2023

24-04-2023 | Regular Paper

Entity graphs for exploring online discourse

Authors: Nicholas Botzer, Tim Weninger

Published in: Knowledge and Information Systems | Issue 9/2023

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Abstract

A vast amount of human communication occurs online. These digital traces of natural human communication along with recent advances in natural language processing technology provide for computational analysis of these discussions. In the study of social networks, the typical perspective is to view users as nodes and concepts as flowing through and among the user nodes within the social network. In the present work, we take the opposite perspective: we extract and organize massive amounts of group discussion into a concept space we call an entity graph where concepts and entities are static and human communicators move about the concept space via their conversations. Framed by this perspective, we performed several experiments and comparative analysis on large volumes of online discourse from Reddit. In quantitative experiments, we found that discourse was difficult to predict, especially as the conversation carried on. We also developed an interactive tool to visually inspect conversation trails over the entity graph; although they were difficult to predict, we found that conversations, in general, tended to diverge to a vast swath of topics initially, but then tended to converge to simple and popular concepts as the conversation progressed. An application of the spreading activation function from the field of cognitive psychology also provided compelling visual narratives from the data.
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Literature
1.
Page R (2015) The narrative dimensions of social media storytelling. In: The handbook of narrative analysis, pp 329–347
2.
Mateas M, Sengers P (2003) Narrative intelligence. John Benjamins Publishing, AmsterdamCrossRef
3.
Chafe W (2017) Language and the flow of thought. The new psychology of language, pp 93–111
4.
Chafe W (1994) Discourse, consciousness, and time: the flow and displacement of conscious experience in speaking and writing. University of Chicago Press, Chicago
5.
Shen W, Wang J, Han J (2014) Entity linking with a knowledge base: issues, techniques, and solutions. IEEE Trans Knowl Data Eng 27(2):443–460CrossRef
6.
Cheng X, Roth D (2013) Relational inference for wikification. In: Empirical methods in natural language processing
7.
Shahaf D et al (2013) Information cartography: creating zoomable, large-scale maps of information. In: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
8.
Shahaf D, Guestrin C (2010) Connecting the dots between news articles. In: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
9.
Keith Norambuena BF, Mitra T (2021) Narrative maps: An algorithmic approach to represent and extract information narratives. In: Proceedings of the ACM on Human–Computer interaction 4 (CSCW3), pp 1–33
10.
Derczynski L et al (2015) Analysis of named entity recognition and linking for tweets. Inf Process Manag 51(2):32–49CrossRef
11.
Ran C, Shen W, Wang J (2018) An attention factor graph model for tweet entity linking. In: Proceedings of the 2018 world wide web conference
12.
13.
Kempe D, Kleinberg J, Tardos É (2003) Maximizing the spread of influence through a social network. In: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
14.
Centola D (2010) The spread of behavior in an online social network experiment. Science 329(5996):1194–1197CrossRef
15.
Schia NN, Gjesvik L (2020) Hacking democracy: managing influence campaigns and disinformation in the digital age. J Cyber Policy 5(3):413–428CrossRef
16.
17.
Glenski M, Ayton E, Mendoza J, Volkova S (2019) Multilingual multimodal digital deception detection and disinformation spread across social platforms. arXiv:​1909.​05838
18.
Cinelli M, De Francisci Morales G, Galeazzi A, Quattrociocchi W, Starnini M (2021) The echo chamber effect on social media. Proc Natl Acad Sci 118(9):e2023301118CrossRef
19.
Garimella K, De Francisci Morales G, Gionis A, Mathioudakis M (2018) Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship
20.
Brady WJ, Crockett MJ, Van Bavel JJ (2020) The mad model of moral contagion: the role of motivation, attention, and design in the spread of moralized content online. Perspect Psychol Sci 15(4):978–1010CrossRef
21.
Iyengar S, Lelkes Y, Levendusky M, Malhotra N, Westwood SJ (2019) The origins and consequences of affective polarization in the United States. Ann Rev Polit Sci 22:129–146CrossRef
22.
Baumgartner J, Zannettou S, Keegan B, Squire M, Blackburn J (2020) The pushshift reddit dataset. In: Proceedings of the international AAAI conference on web and social media
23.
Medvedev AN, Lambiotte R, Delvenne J-C (2017) The anatomy of Reddit: an overview of academic research. Dyn Complex Netw 10:183–204
24.
Zomick J, Levitan SI, Serper M (2019) Linguistic analysis of schizophrenia in reddit posts. In: Proceedings of the 6th workshop on computational linguistics and clinical psychology
25.
Chandrasekharan E et al (2017) You can’t stay here: the efficacy of Reddit’s 2015 ban examined through hate speech. In: Proceedings of the ACM on human–computer interaction 1 (CSCW), pp 1–22
26.
Farrell T, Fernandez M, Novotny J, Alani H (2019) Exploring misogyny across the manosphere in reddit. In: Proceedings of the 10th ACM conference on web science
27.
Tadesse MM, Lin H, Xu B, Yang L (2019) Detection of depression-related posts in reddit social media forum. IEEE Access 7:44883–44893CrossRef
28.
Sevgili O, Shelmanov A, Arkhipov M, Panchenko A, Biemann C (2020) Neural entity linking: a survey of models based on deep learning. arXiv:​2006.​00575
29.
Botzer N, Ding Y, Weninger T (2021) Reddit entity linking dataset. Inf Process Manag 58(3):102479CrossRef
30.
van Hulst JM, Hasibi F, Dercksen K, Balog K, de Vries AP (2020) Rel: an entity linker standing on the shoulders of giants
31.
Zien JY, Schlag MD, Chan PK (1999) Multilevel spectral hypergraph partitioning with arbitrary vertex sizes. IEEE Trans Comput Aided Des Integr Circuits Syst 18(9):1389–1399CrossRef
32.
33.
34.
Zhang H, Liu Z, Xiong C, Liu Z (2019) Grounded conversation generation as guided traverses in commonsense knowledge graphs. arXiv:​1911.​02707
35.
Moon S, Shah P, Kumar A, Subba R (2019) Opendialkg: explainable conversational reasoning with attention-based walks over knowledge graphs. In: Proceedings of the 57th annual meeting of the association for computational linguistics
36.
Jung J, Son B, Lyu S (2020) Attnio: Knowledge graph exploration with in-and-out attention flow for knowledge-grounded dialogue. In: Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP)
37.
Kusner M, Sun Y, Kolkin N, Weinberger, K (2015) From word embeddings to document distances. In: International conference on machine learning
38.
Fruchterman TM, Reingold EM (1991) Graph drawing by force-directed placement. Softw Pract Exp 21(11):1129–1164CrossRef
39.
Bostock M, Ogievetsky V, Heer J (2011) D\(^3\) data-driven documents. IEEE Trans Vis Comput Graph 17(12):2301–2309CrossRef
40.
Collins AM, Loftus EF (1975) A spreading-activation theory of semantic processing. Psychol Rev 82(6):407CrossRef
41.
Paul C, Matthews M (2016) The russian “firehose of falsehood’’ propaganda model. Rand Corp 2(7):1–10
42.
Huddy L, Khatib N (2007) American patriotism, national identity, and political involvement. Am J Polit Sci 51(1):63–77CrossRef
43.
De Cleen B (2017) Populism and nationalism. The Oxford handbook of populism 1:342–262
44.
Rao A et al (2021) Political partisanship and antiscience attitudes in online discussions about COVID-19: Twitter content analysis. J Med Internet Res 23(6):e26692CrossRef
45.
Kalantari N, Liao D, Motti VG (2021) Characterizing the online discourse in Twitter: Users’ reaction to misinformation around COVID-19 in Twitter
46.
Guntuku SC, Buttenheim AM, Sherman G, Merchant RM (2021) Twitter discourse reveals geographical and temporal variation in concerns about COVID-19 vaccines in the United States. Vaccine 39(30):4034–4038CrossRef
47.
Ilievski F, Vossen P, Schlobach S (2018) Systematic study of long tail phenomena in entity linking. In: Proceedings of the 27th international conference on computational linguistics
48.
Metadata
Title
Entity graphs for exploring online discourse
Authors
Nicholas Botzer
Tim Weninger
Publication date
24-04-2023
Publisher
Springer London
Published in
Knowledge and Information Systems / Issue 9/2023
Print ISSN: 0219-1377
Electronic ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-023-01877-8

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