Overview of the Multimedia Information Processing for Personality & Social Networks Analysis Contest
Progress in the autonomous analysis of human behavior from multimodal information has lead to very effective methods able to deal with problems like action/gesture/activity recognition, pose estimation, opinion mining, user tailored retrieval, etc. However, it is only recently that the community has been starting to look into related problems associated with more complex behavior, including personality analysis, deception detection, among others. We organized an academic contest co-located with ICPR2018 running two tasks in this direction. On the one hand, we organized an information fusion task in the context of multimodal image retrieval in social media. On the other hand, we ran another task in which we aim to infer personality traits from written essays, including textual and handwritten information. This paper describes both tasks, detailing for each of them the associated problem, data sets, evaluation metrics and protocol, as well as an analysis of the performance of simple baselines.
KeywordsInformation fusion Personality analysis Social networks Handwritten recognition Multimedia information processing
Gabriela Ramirez and Esaú Villatoro would like to thank the UAM-C for the facilities provided in this project. Their research was partially supported by CONACYT-Mexico under project grant 258588 and under the Thematic Networks program (Language Technologies Thematic Network, project 281795). Bogdan Ionescu’s work was supported by the Romanian Ministry of Innovation and Research, UEFISCDI, project SPIA-VA, agreement 2SOL/2017, grant PN-III-P2-2.1-SOL-2016-02-0002. We would like also to acknowledge the contribution of the task co-organizers: Andrei Jitaru and Liviu Daniel Stefan, University Politehnica of Bucharest, Romania. Hugo Jair Escalante was supported by INAOE. Sergio Escalera’s work has been partially supported by the Spanish project TIN2016-74946-P (MINECO/FEDER, UE) and CERCA Programme / Generalitat de Catalunya.
- 3.Gosling, S.D., Rentfrow Jr., P.J., Swann, W.B.: A very brief measure of the big-five personality domains. J. Res. Pers. 37(6), 504–528 (2003). https://doi.org/10.1016/S0092-6566(03)00046-1. http://www.sciencedirect.com/science/article/pii/S0092656603000461CrossRefGoogle Scholar
- 4.Ionescu, B., Gînscă, A.L., Zaharieva, M., Boteanu, B.A., Lupu, M., Müller, H.: Retrieving diverse social images at MediaEval 2016: challenge, dataset and evaluation. In: MediaEval 2016 Workshop (2016)Google Scholar
- 5.Ionescu, B., Gînscă, A.L., Boteanu, B., Lupu, M., Popescu, A., Müller, H.: Div150multi: a social image retrieval result diversification dataset with multi-topic queries. In: International Conference on Multimedia Systems, pp. 46:1–46:6 (2016)Google Scholar
- 6.Ionescu, B., Popescu, A., Lupu, M., Gînscă, A.L., Boteanu, B., Müller, H.: Div150cred: a social image retrieval result diversification with user tagging credibility dataset. In: ACM Multimedia Systems Conference, pp. 207–212 (2015)Google Scholar
- 7.Ionescu, B., Radu, A.L., Menéndez, M., Müller, H., Popescu, A., Loni, B.: Div400: a social image retrieval result diversification dataset. In: ACM Multimedia Systems Conference, pp. 29–34 (2014)Google Scholar
- 9.Pennebaker, J.W.: The Secret Life of Pronouns: What Our Words Say About Us, 1st edn. Bloomsbury Press, New York (2011)Google Scholar
- 10.Ramírez-de-la-Rosa, G., Villatoro-Tello, E., Jiménez-Salazar, H.: TxPIu: a resource for personality identication of undergraduates. J. Intell. Fuzzy Syst. 34(5), 2991–3001 (2018). https://doi.org/10.3233/JIFS-169484, https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs169484CrossRefGoogle Scholar
- 11.Sabetghadam, S., Palotti, J., Rekabsaz, N., Lupu, M., Hanbury, A.: TUW @ MediaEval 2015 retrieving diverse social images task. In: MediaEval 2015 Workshop (2015)Google Scholar