The Signos data have been collected within a study analyzing personal networks of immigrants in Barcelona using the EgoNet software. The study has been conducted by EgoLab and funded by the Fundació ACSAR pel Comissionat per Immigració i Diàleg Intercultural de l’Ajuntament de Barcelona. For more on this study and its outcome see the book (in Catalan): Jose Luis Molina and Fabien Pelissier (eds.) (2010). Les xarxes socials de sikhs, xinesos i filipins a Barcelona. Barcelona: Fundació ACSAR. (Also see the list of EgoLab projects.)
We provide the data here for illustrative purposes; for more personal network data and background see the Observatory of Personal Networks (OPeN).
The data consists of 70 EgoNet interviews obtained from Chinese (21), Philippine (25), and Sikh (24) immigrants in Barcelona. Each respondent (ego) has answered four types of questions:
- questions about ego, including country of origin, years of residence, age, gender, religion, reasons for migrating, ...
- alters a list of 30 persons known to ego; the alters are the nodes in the personal network
- questions about alters including country of origin, country of residence, age, type of relation to ego, ...
- alter-alter ties (undirected) pairs of alters that know each other (according to the respondent)
Alter names have been replaced by numerical ids (0,1,...,29) and ego names by numerical ids preceeded by the terms chinese, filipinos, or sikhs, depending on the community.
signos_public_data contains two study definition files
.ego files define the questionnaire, i.e., the questions and (if applies) a list of potential answers. In the
interviews-directory there are three subfolders
sikhs containing the interview files (
*.int) for the three communities. Each
.int-file contains the answers of one respondent and, thus, defines a personal network. Most interviews have been conducted with the
signos.ego questionnaire; few with the
signos_p_piloto.ego. (This distinction is only relevant if you open the interviews with the EgoNet software; not for the EgoNet2GraphML converter.)