Center for Humans and Machines
Publications 2020-2022/23

Alfonseca, M., Cebrian, M., Anta, A. F., Coviello, L., Abeliuk, A., & Rahwan, I. (2021). Superintelligence cannot be contained: Lessons from computability theory. Journal of Artificial Intelligence Research, 70, 65–76. https://doi.org/10.1613/jair.1.12202

Avraam, D., Obradovich, N., Pescetelli, N., Cebrian, M., & Rutherford, A. (2021). The network limits of infectious disease control via occupation-based targeting. Scientific Reports, 11, Article 22855. https://doi.org/10.1038/s41598-021-02226-x

Bassett, J., Gethmann, J., Blunk, P., Conraths, F. J., & Hövel, P. (2021). Individual-based model for the control of Bovine Viral Diarrhea spread in livestock trade networks. Journal of Theoretical Biology, 527, Article 110820. https://doi.org/10.1016/j.jtbi.2021.110820

Bassett, J., Pescetelli, N., Rutherford, A., & Cebrian, M. (2021). Time-critical decentralised situational awareness in emergencies: An adversarial biosecurity scenario. Applied Network Science, 6, Article 59. https://doi.org/10.1007/s41109-021-00402-6

Cebrian, M. (2021). The past, present and future of digital contact tracing. Nature Electronics, 4, 2–4. https://doi.org/10.1038/s41928-020-00535-z

Cebrian, M. (2021). A time-critical crowdsourced computational search for the origins of COVID-19. Nature Electronics, 4, 450–451. https://doi.org/10.1038/s41928-021-00619-4

Chen, H., Kryvasheyeu, Y., Xu, W., Huang, Y., Deng, J., Ren, S., Li, X., Rahwan, I., & Cebrian, M. (2021). Evolution of urban forms observed from space. EPJ Data Science, 10, Article 27. https://doi.org/10.1140/epjds/s13688-021-00283-w

Cuomo, R. E., Purushothaman, V. L., Li, J., Bardier, C., Nali, M., Shah, N., Obradovich, N., Yang, J., & Mackey, T. K. (2021). Characterizing self-reported tobacco, vaping, and marijuana-related tweets geolocated for California college campuses. Frontiers in Public Health, 9, Article 628812. https://doi.org/10.3389/fpubh.2021.628812

Dhaliwal, N. A., Patil, I., & Cushman, F. (2021). Reputational and cooperative benefits of third-party compensation. Organizational Behavior and Human Decision Processes, 164, 27–51. https://doi.org/10.1016/j.obhdp.2021.01.003

Dong, M., Palomo‐Vélez, G., & Wu, S. (2021). Reducing the gap between pro‐environmental disposition and behavior: The role of feeling power. Journal of Applied Social Psychology, 51(3), 262–272. https://doi.org/10.1111/jasp.12733

Dong, M., Spadaro, G., Yuan, S., Song, Y., Ye, Z., & Ren, X. (2021). Self-interest bias in the COVID-19 pandemic: A cross-cultural comparison between the United States and China. Journal of Cross-Cultural Psychology, 52(7), 663–679. https://doi.org/10.1177/00220221211025739

Dong, M., van Prooijen, J.-W., & van Lange, P. A. M. (2021). Calculating Hypocrites Effect: Moral judgments of word-deed contradictory transgressions depend on targets' competence. Journal of Theoretical Social Psychology, 5(4), 489–501. https://doi.org/10.1002/jts5.113

Ferreira, L. N., Hong, I., Rutherford, A., & Cebrian, M. (2021). The small-world network of global protests. Scientific Reports, 11, Article 19215. https://doi.org/10.1038/s41598-021-98628-y

Fowler, J. H., Hill, S. J., Levin, R., & Obradovich, N. (2021). Stay-at-home orders associate with subsequent decreases in COVID-19 cases and fatalities in the United States. PLoS ONE, 16(6), Article e0248849. https://doi.org/10.1371/journal.pone.0248849

Groh, M., Epstein, Z., Obradovich, N., Cebrian, M., & Rahwan, I. (2021). Human detection of machine-manipulated media. Communications of the ACM, 64(10), 40–47. https://doi.org/10.1145/3445972

Hong, I., Rutherford, A., & Cebrian, M. (2021). Social mobilization and polarization can create volatility in COVID‑19 pandemic control. Applied Network Science, 6, Article 11. https://doi.org/10.1007/s41109-021-00356-9

Klockmann, V., von Schenk, A., & von Siemens, F. A. (2021). Division of labor and the organization of knowledge in production: A laboratory experiment. Games and Economic Behavior, 130, 196–210. https://doi.org/10.1016/j.geb.2021.08.002

Köbis, N., Bonnefon, J.-F., & Rahwan, I. (2021). Bad machines corrupt good morals. Nature Human Behaviour, 5(6), 679–685. https://doi.org/10.1038/s41562-021-01128-2

Köbis, N. C., Doležalová, B., & Soraperra, I. (2021). Fooled twice: People cannot detect deepfakes but think they can. iScience, 24(11), Article 103364. https://doi.org/10.1016/j.isci.2021.103364

Köbis, N., & Mossink, L. D. (2021). Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry. Computers in Human Behavior, 114, Article 106553. https://doi.org/10.1016/j.chb.2020.106553

Kwon, O.-H., Hong, I., Yang, J., Wohn, D. Y., Jung, W.-S., & Cha, M. (2021). Urban green space and happiness in developed countries. EPJ Data Science, 10, Article 28. https://doi.org/10.1140/epjds/s13688-021-00278-7

Laakasuo, M., Palomäki, J., & Köbis, N. (2021). Moral uncanny valley: A robot’s appearance moderates how its decisions are judged. International Journal of Social Robotics, 13, 1679–1688. https://doi.org/10.1007/s12369-020-00738-6

Leib, M., Köbis, N., Soraperra, I., Weisel, O., & Shalvi, S. (2021). Collaborative dishonesty: A meta-analytic review. Psychological Bulletin, 147(12), 1241–1268. https://doi.org/10.1037/bul0000349

Li, C., Wei, W., Feng, X., & Liu, J. (2021). Research of motif-based similarity for link prediction problem. IEEE Access, 9, 66636–66645. https://doi.org/10.1109/ACCESS.2021.3077016

Li, X., Wei, W., Feng, X., Liu, X., & Zheng, Z. (2021). Representation learning of graphs using graph convolutional multilayer networks based on motifs. Neurocomputing, 464, 218–226. https://doi.org/10.1016/j.neucom.2021.08.028

Ligo, A. K., Rand, K., Bassett, J., Galaitsi, S. E., Trump, B. D., Jayabalasingham, B., Collins, T., & Linkov, I. (2021). Comparing the emergence of technical and social sciences research in artificial intelligence. Frontiers in Computer Science, 3, Article 653235. https://doi.org/10.3389/fcomp.2021.653235

Liu, X., Wei, W., Feng, X., Cao, X., & Sun, D. (2021). Graph classification based on skeleton and component features. Knowledge-Based Systems, 228, Article 107301. https://doi.org/10.1016/j.knosys.2021.107301

Lüdecke, D., Ben-Shachar, M. S., Patil, I., Waggoner, P., & Makowski, D. (2021). performance: An R package for assessment, comparison and testing of statistical models. Journal of Open Source Software, 6(60), Article 3139. https://doi.org/10.21105/joss.03139

Lüdecke, D., Patil, I., Ben-Shachar, M. S., Wiernik, B. M., Waggoner, P., & Makowski, D. (2021). see: An R package for visualizing statistical models. Journal of Open Source Software, 6(64), Article 3393. https://doi.org/10.21105/joss.03393

Moro, E., Frank, M. R., Pentland, A., Rutherford, A., Cebrian, M., & Rahwan, I. (2021). Universal resilience patterns in labor markets. Nature Communications, 12, Article 1972. https://doi.org/10.1038/s41467-021-22086-3

Müller, T. F., Winters, J., Morisseau, T., Noveck, I., & Morin , O. (2021). Colour terms: Native language semantic structure and artificial language structure formation in a large-scale online smartphone application. Journal of Cognitive Psychology, 33(4), 357–378. https://doi.org/10.1080/20445911.2021.1900199

Patil, I. (2021). statsExpressions: R package for tidy dataframes and expressions with statistical details. Journal of Open Source Software, 6(61), Article 3236. https://doi.org/10.21105/joss.03236

Patil, I. (2021). Visualizations with statistical details: The 'ggstatsplot' approach. Journal of Open Source Software, 6(61), Article 3167. https://doi.org/10.21105/joss.03167

Patil, I., Larsen, E. M., Kichic, R., & Gleichgerrcht, E. (2021). Moral cognition about harm in anxiety disorders: The importance of experienced emotion. Psychological Reports, 124(6), 2501–2523. https://doi.org/10.1177/0033294120964134

Patil, I., & Trémolière, B. (2021). Reasoning supports forgiving accidental harms. Scientific Reports, 11, Article 14418. https://doi.org/10.1038/s41598-021-93908-z

Pescetelli, N., Hauperich, A.-K., & Yeung, N. (2021). Confidence, advice seeking and changes of mind in decision making. Cognition, 215, Article 104810. https://doi.org/10.1016/j.cognition.2021.104810

Pescetelli, N., Rutherford, A., & Rahwan, I. (2021). Modularity and composite diversity affect the collective gathering of information online. Nature Communications, 12, Article 3195. https://doi.org/10.1038/s41467-021-23424-1

Pescetelli, N., & Yeung, N. (2021). The role of decision confidence in advice-taking and trust formation. Journal of Experimental Psychology: General, 150(3), 507–526. https://doi.org/10.1037/xge0000960

Romanello, M., McGushin, A., Di Napoli, C., Drummond, P., Hughes, N., Jamart, L., Kennard, H., Lampard, P., Rodriguez, B. S., Arnell, N., Ayeb-Karlsson, S., Belesova, K., Cai, W., Campbell-Lendrum, D., Capstick, S., Chambers, J., Chu, L., Ciampi, L., Dalin, C., Dasandi, N., Dasgupta, S., Davies, M., Dominguez-Salas, P., Dubrow, R., Ebi, K. L., Eckelman, M., Ekins, P., Escobar, L. E., Georgeson, L., Grace, D., Graham, H., Gunther, S. H., Hartinger, S., He, K., Heaviside, C., Hess, J., Hsu, S.-C., Jankin, S., Jimenez, M. P., Kelman, I., Kiesewetter, G., Kinney, P. L., Kjellstrom, T., Kniveton, D., Lee, J. K. W., Lemke, B., Liu, Y., Liu, Z., Lott, M., Lowe, R., Martinez-Urtaza, J., Maslin, M., McAllister, L., McMichael, C., Mi, Z., Milner, J., Minor, K., Mohajeri, N., Moradi-Lakeh, M., Morrissey, K., Munzert, S., Murray, K. A., Neville, T., Nilsson, M., Obradovich, N., Sewe, M. O., Oreszczyn, T., Otto, M., Owfi, F., Pearman, O., Pencheon, D., Rabbaniha, M., Robinson, E., Rocklov, J., Salas, R. N., Semenza, J. C., Sherman, J., Shi, L., Springmann, M., Tabatabaei, M., Taylor, J., Trinanes, J., Shumake-Guillemot, J., Vu, B., Wagner, F., Wilkinson, P., Winning, M., Yglesias, M., Zhang, S., Gong, P., Montgomery, H., Costello, A., & Hamilton, I. (2021). The 2021 report of the Lancet Countdown on health and climate change: Code red for a healthy future. The Lancet, 398(10311), 1619–1662. https://doi.org/10.1016/S0140-6736(21)01787-6

Sarkadi, Ş., Rutherford, A., McBurney, P., Parsons, S., & Rahwan, I. (2021). The evolution of deception. Royal Society Open Science, 8, Article 201032. https://doi.org/10.1098/rsos.201032

Saveski, M., Awad, E., Rahwan, I., & Cebrian, M. (2021). Algorithmic and human prediction of success in human collaboration from visual features. Scientific Reports, 11, Article 2756. https://doi.org/10.1038/s41598-021-81145-3

Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2021). How safe is safe enough? Psychological mechanisms underlying extreme safety demands for self-driving cars. Transportation Research Part C: Emerging Technologies, 126, Article 103069. https://doi.org/10.1016/j.trc.2021.103069

Sorokowska, A., Saluja, S., Sorokowski, P., Frąckowiak, T., Karwowski, M., Aavik, T., Akello, G., Alm, C., Amjad, N., Anjum, A., Asao, K., Atama, C. S., Duyar, D. A., Ayebare, R., Batres, C., Bendixen, M., Bensafia, A., Bizumic, B., Boussena, M., Buss, D. M., Butovskaya, M., Can, S., Cantarero, K., Carrier, A., Cetinkaya, H., Chabin, D., Conroy-Beam, D., Contreras-Graduño, J., Varella, M. A. C., Cueto, R. M., Czub, M., Dronova, D., Dural, S., Duyar, I., Ertugrul, B., Espinosa, A., Esteves, C. S., Guemaz, F., Hal'amová, M., Herak, I., Hromatko, I., Hui, C.-M., Jaafar, J. L., Jiang, F., Kafetsios, K., Kavcic, T., Kennair, L. E. O., Kervyn, N. O., Khilji, I. A., Köbis, N. C., Kostic, A., Láng, A., Lennard, G. R., León, E., Lindholm, T., Lopez, G., Manesi, Z., Martinez, R., McKerchar, S. L., Meskó, N., Misra, G., Monaghan, C., Mora, E. C., Moya-Garofano, A., Musil, B., Natividade, J. C., Nizharadze, G., Oberzaucher, E., Oleszkiewicz, A., Onyishi, I. E., Özener, B., Pagani, A. F., Pakalniskiene, V., Parise, M., Pazhoohi, F., Pejičić, M., Pisanski, A., Pisanski, K., Plohl, N., Popa, C., Prokop, P., Rizwan, M., Sainz, M., Salkičević, S., Sargautyte, R., Sarmany-Schuller, I., Schmehl, S., Shahid, A., Shaikh, R., Sharad, S., Siddiqui, R. S., Simonetti, F., Tadinac, M., González, K. U., Uhryn, O., Vauclair, C.-M., Araya, L. D. V., Widarini, D. A., Yoo, G., Zadeh, Z. F., Zat'ková, M., Zupančič, M., & Croy, I. (2021). Affective interpersonal touch in close relationships: A cross-cultural perspective. Personality and Social Psychology Bulletin, 47(12), 1705–1721. https://doi.org/10.1177/0146167220988373

Xu, W., Qin, X., Li, X., Chen, H., Frank, M., Rutherford, A., Reeson, A., & Rahwan, I. (2021). Developing China's workforce skill taxonomy reveals extent of labor market polarization. Humanities and Social Sciences Communications, 8, Article 187. https://doi.org/10.1057/s41599-021-00862-2

Yang, J. S., Cuomo, R. E., Purushothaman, V., Nali, M., Shah, N., Bardier, C., Obradovich, N., & Mackey, T. (2021). Campus smoking policies and smoking-related Twitter posts originating from California public universities: Retrospective study. JMIR Formative Research, 5(12), Article e33331. https://doi.org/10.2196/33331

Jung, C., Hong, I., Sáez-Trumper, D., Lee, D., Myung, J., Kim, D., Yun, J., Jung, W.-S., & Cha, M. (2021). Information flow on COVID-19 over Wikipedia: A case study of 11 languages. In WWW '21: Companion Proceedings of the Web Conference 2021. Ljubljana, Slovenia, April 19 - 23, 2021 (pp. 627–628). International World Wide Web Conferences Committee. https://doi.org/10.1145/3442442.3452352

Köbis, N., Bonnefon, J.-F., & Rahwan, I. (2021). Bad machines corrupt good morals (TSE Working Papers No. 1212). Toulouse School of Economics.

Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2021). “How safe is safe enough? Psychological mechanisms underlying extreme safety demands for self-driving cars” (TSE Working Papers No. 1215). Toulouse School of Economics.