Mao R, Wang T, Cambria E. Decoding metaphors and brain signals in naturalistic contexts: An empirical study based on EEG and MetaPro. In: Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci). San Francisco, United States; 2025. p. 303–310.

Mao R, Zhang T, Liu Q, Hussain A, Cambria E. Unveiling diplomatic narratives: Analyzing United Nations Security Council debates through metaphorical cognition. In: Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci), vol. 46. Rotterdam, the Netherlands; 2024. p. 1709–1716.

Rapaport D, Gill M, Schafer R. Diagnostic psychological testing: The theory, statistical evaluation, and diagnostic application of a battery of tests. Am J Psychol. 1946;2.

Lakoff G, Johnson M. Metaphors We Live By. Chicago, U.S.: The University of Chicago Press; 1980.

Google Scholar 

Mao R, Li X, He K, Ge M, Cambria E. MetaPro Online: A computational metaphor processing online system. In: Proceedings of the 61st annual meeting of the association for computational linguistics, vol. 3. 2023. p. 127–135.

Carracedo P, Puertas R, Marti L. Research lines on the impact of the COVID-19 pandemic on business. a text mining analysis. J Bus Res. 2021;132:586–93.

Article  Google Scholar 

Yang M, Han C. Revealing industry challenge and business response to covid-19: a text mining approach. Int J Contemp Hosp Manag. 2021;33(4):1230–48.

Article  Google Scholar 

Praveen S, Ittamalla R, Deepak G. Analyzing the attitude of indian citizens towards COVID-19 vaccine-a text analytics study. Diabetes Metab Syndr. 2021;15(2):595–9.

Article  Google Scholar 

Wankhade M, Rao ACS, Kulkarni C. A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev. 2022;55(7):5731–80.

Article  Google Scholar 

Zad S, Heidari M, James Jr H, Uzuner O. Emotion detection of textual data: An interdisciplinary survey. In: AIIoT. 2021.

Wang LL, Lo K. Text mining approaches for dealing with the rapidly expanding literature on COVID-19. Brief. Bioinformatics 2021;22.

Roberts ME, Stewart BM, Tingley D, et al. Structural topic models for open-ended survey responses. AJPS. 2014;58(4):1064–82.

Google Scholar 

Glowacki EM, Wilcox GB, Glowacki JB. Identifying #addiction concerns on twitter during the COVID-19 pandemic: A text mining analysis. Subst Abus. 2021;42(1):39–46.

Article  Google Scholar 

Ranjbari M, Esfandabadi ZS, Gautam S, et al. Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses. Gondwana Res. 2023;114:124–37.

Article  Google Scholar 

Semino E. “Not soldiers but fire-fighters”-metaphors and Covid-19. Health Commun. 2021;36(1):50–8.

Castro Seixas E. War metaphors in political communication on COVID-19. Front Sociol. 2021;5:583680.

Article  Google Scholar 

Wicke P, Bolognesi MM. Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PloS One. 2020;15(9):0240010.

Article  Google Scholar 

Cambria E, Zhang X, Mao R, Chen M, Kwok K. SenticNet 8: Fusing emotion AI and commonsense AI for interpretable, trustworthy, and explainable affective computing. In: Proceedings of International Conference on Human-Computer Interaction (HCII), Washington DC, USA; 2024. p. 197–216

Fan C, Lin J, Mao R, Cambria E. Fusing pairwise modalities for emotion recognition in conversations. Inform Fus. 2024;106:102306.

Article  Google Scholar 

Mao R, Liu Q, He K, Li W, Cambria E. The biases of pre-trained language models: An empirical study on prompt-based sentiment analysis and emotion detection. IEEE Trans Affect Comput. 2023;14(3):1743–53.

Article  Google Scholar 

Han S, Mao R, Cambria E. Hierarchical attention network for explainable depression detection on Twitter aided by metaphor concept mappings. In: COLING. 2022. p. 94–104.

Ji S, Pan S, Li X, Cambria E, Long G, Huang Z. Suicidal ideation detection: A review of machine learning methods and applications. IEEE Trans Comput Soc. 2020;8(1):214–26.

Article  Google Scholar 

Karami A, Zhu M, Goldschmidt B, et al. COVID-19 vaccine and social media in the US: Exploring emotions and discussions on Twitter. Vaccines. 2021;9(10):1059.

Article  Google Scholar 

Xia E, Yue H, Liu H. Tweet sentiment analysis of the 2020 US presidential election. In: Web Conf. 2021. p. 367–371.

Duong C, Raghuram VC, Lee A, Mao R, Mengaldo G, Cambria E. Neurosymbolic AI for mining public opinions about wildfires. Cognitive Comput. 2024;16:1531–53.

Article  Google Scholar 

Garcia MB, Cunanan-Yabut A. Public sentiment and emotion analyses of Twitter data on the 2022 Russian invasion of Ukraine. In: ICITACEE. 2022. p. 242–247.

Mao R, Li X. Bridging towers of multi-task learning with a gating mechanism for aspect-based sentiment analysis and sequential metaphor identification. In: AAAI, vol. 35. 2021. p. 13534–13542.

Liu Y, Ott M, Goyal N, Du J, Joshi M, Chen D, Levy O, Lewis M, Zettlemoyer L, Stoyanov V. RoBERTa: A robustly optimized bert pretraining approach. 2019. arXiv preprint arXiv:1907.11692

Miller GA. WordNet: a lexical database for English. Commun ACM. 1995;38(11):39–41.

Article  Google Scholar 

Mao R, Li X, Ge M, Cambria E. MetaPro: A computational metaphor processing model for text pre-processing. Inf Fus. 2022;86-87.

Ge M, Mao R, Cambria E. Explainable metaphor identification inspired by conceptual metaphor theory. In: AAAI, vol. 36. 2022.

Pragglejaz G. MIP: A method for identifying metaphorically used words in discourse. Metaphor Symb. 2007;22(1):1–39.

Google Scholar 

Bailey SC, Serper M, Opsasnick L, et al. Changes in COVID-19 knowledge, beliefs, behaviors, and preparedness among high-risk adults from the onset to the acceleration phase of the us outbreak. J Gen Intern Med. 2020;35:3285–92.

Article  Google Scholar 

Gerlich M. COVID-19 induced changes in consumer behavior. OJBM. 2021;9(5).

Kontis V, Bennett JE, Rashid T, et al. Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries. Nat Med. 2020;26(12):1919–28.

Article  Google Scholar 

Talmy L. Lexicalization patterns: Semantic structure in lexical forms. Lang Typol Syntactic Descript. 1985;3(99):36–149.

Google Scholar 

Rappaport Hovav M, Levin B. Building verb meanings. Project Argum: Lexical Composit Fact. 1998;97–134.

Mao R, Du K, Ma Y, Zhu L, Cambria E. Discovering the cognition behind language: Financial metaphor analysis with MetaPro. In: IEEE ICDM. 2023.

Mao R, Lin Q, Liu Q, Mengaldo G, Cambria E. Understanding public perception towards weather disasters through the lens of metaphor. In: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI). Jeju, South Korea; 2024. p. 7394–7402.

Hampshire A, Hellyer PJ, Soreq E et al. Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom. Nat Commun. 2021;12.

Woods JA, Hutchinson NT, Powers SK, et al. The COVID-19 pandemic and physical activity. Sports Med Health Sci. 2020;2(2):55–64.

Article  Google Scholar 

Clark-Ginsberg A, Petrun Sayers EL. Communication missteps during COVID-19 hurt those already most at risk. JCCM. 2020;28(4):482–4.

Google Scholar 

He X, Lau EH, Wu P, et al. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat Med. 2020;26(5):672–5.

Article  Google Scholar 

Walsh F. Loss and resilience in the time of COVID-19: Meaning making, hope, and transcendence. Fam Process. 2020;59(3):898–911.

Article  Google Scholar 

Jeffrey DI. Relational ethical approaches to the COVID-19 pandemic. J Med Ethics. 2020.

Litton MM, Beavers AW. The relationship between food security status and fruit and vegetable intake during the COVID-19 pandemic. Nutrients. 2021;13(3):712.

Article  Google Scholar 

Gallotti R, Valle F, Castaldo N, Sacco P, De Domenico M. Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics. Nat Hum Behav. 2020;4(12):1285–93.

Dalglish SL. COVID-19 gives the lie to global health expertise. The Lancet. 2020;395(10231).

Lavazza A, Farina M. The role of experts in the COVID-19 pandemic and the limits of their epistemic authority in democracy. Front Public Health. 2020;8:356.

Article  Google Scholar 

Li J, Giabbanelli P. Returning to a normal life via COVID-19 vaccines in the united states: a large-scale agent-based simulation study. JMIR Med Inform. 2021;9(4):27419.

Article  Google Scholar 

Ernst M, Niederer D, Werner AM, et al. Loneliness before and during the COVID-19 pandemic: A systematic review with meta-analysis. Am Psychol. 2022;77(5):660.

Article  Google Scholar 

Juliano C, Castrucci B, Fraser MR. COVID-19 and public health: looking back, moving forward. Lippincott Williams & Wilkins; 2021.

Bolsen T, Palm R. Politicization and COVID-19 vaccine resistance in the US. PMBTS. 2022;188(1):81–100.

Google Scholar 

Bernardi L, Sala G, Gotlib IH. A cognitive model of depression and political attitudes. Elector Stud. 2024;87:102737.

Article  Google Scholar 

Havey NF. Partisan public health: how does political ideology influence support for COVID-19 related misinformation? J Comput Soc Sci. 2020;3.

Warden CA, Warden AR, Huang SC-T, Chen JF. Job tension and emotional sensitivity to COVID-19 public messaging and risk perception. Popul Health Manag. 2021;24.

Carter DP, May PJ. Making sense of the US COVID-19 pandemic response: A policy regime perspective. Adm Theory Prax. 2020;42.

Lyon RF. The COVID-19 response has uncovered and increased our vulnerability to biological warfare. Mil Med. 2021;186(7–8):193–6.

Article  Google Scholar 

Altig D, Baker S, Barrero JM, et al. Economic uncertainty before and during the COVID-19 pandemic. J Public Econ. 2020;191:104274.

Article  Google Scholar 

Ye M. The COVID-19 effect: US-China narratives and realities. Wash Q. 2021;44(1):89–105.

Article  Google Scholar 

Abbas AM, AbouBakr A, Magdy S, et al. Psychological effect of COVID-19 on medical health-care workers. Int J Psychiatry Clin Pract. 2021;25(2):140–1.

Article  Google Scholar 

Pessar SC, Boustead A, Ge Y, Smart R, Pacula RL. Assessment of state and federal health policies for opioid use disorder treatment during the COVID-19 pandemic and beyond. In: JAMA Health Forum, vol. 2. 2021.

Repucci S, Slipowitz A. Democracy under lockdown: The impact of covid-19 on the global struggle for freedom. Freedom House: Technical report; 2020.

Google Scholar 

Byttebier K. COVID-19 and Capitalism: Success and Failure of the Legal Methods for Dealing with a Pandemic. London, UK: Springer; 2022.

Book  Google Scholar