arXiv subjects

Juan C. Losada

Publications and source records attributed to Juan C. Losada.

4 recordsLinked to original sources

arXiv2026

Relationship between ideology and language in the Catalan independence context

Political polarization generates strong effects on society, driving controversial debates and influencing the institutions. Territorial disputes are one of the most important polarized scenarios and have been consistently related to the use of language. In this work, we analyzed the opinion and language distributions through Twitter data of a particular territorial dispute around the independence of Catalonia. We infer a continuous opinion distribution by applying a model based on retweet interactions, previously detecting elite users with fixed and antagonist opinions. The resulting distribution presents a mainly bimodal behavior with an intermediate third pole that shows a less polarized society with the presence of not only antagonist opinions. We find that the more active, engaged and influential users hold more extreme positions. Also we prove that there is a clear relationship between political positions and the use of language, showing that against independence users speak mainly Spanish while pro-independence users speak Catalan and Spanish almost indistinctly. However, the third pole, closer in political opinion to the pro-independence pole, behaves similarly to the against-independence one concerning the use of language.

physics.soc-ph↗

arXiv2026

Impact of individual actions on the collective response of social systems

In a social system individual actions have the potential to trigger spontaneous collective reactions. The way and extent to which the activity (number of actions$-A$) of an individual causes or is connected to the response (number of reactions$-R$) of the system is still an open question. We measure the relationship between activity and response with the distribution of efficiency, a metric defined as $η=R/A$. Generalizing previous results, we show that the efficiency distribution presents a universal structure in three systems of different nature: Twitter, Wikipedia and the scientific citations network. To understand this phenomenon, we develop a theoretical framework composed of three minimal statistical models that contemplate different levels of dependence between $A$ and $R$. The models not only are able to reproduce the empirical activity-response data but also can serve as baselines or null models for more elaborated and domain-specific approaches.

physics.soc-ph↗

arXiv2026

Recurrent patterns of user behavior in different electoral campaigns: A Twitter analysis of the Spanish general elections of 2015 and 2016

We have retrieved and analyzed several millions of Twitter messages corresponding to the Spanish General elections held on the 20th of December 2015 and repeated on the 26th of June 2016. The availability of data from two electoral campaigns that are very close in time allows us to compare collective behaviors of two analogous social systems with a similar context. By computing and analyzing the time series of daily activity, we have found a significant linear correlation between both elections. Additionally, we have revealed that the daily number of tweets, retweets and mentions follow a power law with respect to the number of unique users that take part in the conversation. Furthermore, we have verified that the topologies of the networks of mentions and retweets do not change from one election to the other, indicating that their underlying dynamics are robust in the face of a change in social context. Hence, in the light of our results, there are several recurrent collective behavioral patterns that exhibit similar and consistent properties in different electoral campaigns.

physics.soc-ph↗

arXiv2022

Multipolar social systems: Measuring polarization beyond dichotomous contexts

Social polarization is a growing concern worldwide, as it strains social relations, erodes trust in institutions, and thus threatens democratic societies. Academic efforts to understand this phenomenon have traditionally approached it from a one-dimensional perspective, focusing on bipolar or dichotomous systems. However, political conflicts often involve not only two, but multiple potentially dissenting factions. The most representative examples are multi-party democracies, where the multilateral tensions among different parties often lead to gridlock and uncertainty. Despite the prevalence of these multipolar systems, there is still a lack of suitable analytical tools to study their intricate polarization patterns. In this work, we develop an analytical framework consisting of an inherently multipolar model for unbiased ideological spaces, a method to infer multidimensional opinions from interaction networks, and novel multidimensional polarization metrics that quantify several aspects of ideological polarization and bring new insights into the analysis of high-dimensional opinion distributions. Crucially, our multidimensional framework does not assume the underlying ideological structure, such as conservative vs progressive, liberal vs authoritarian, etc. Instead, it reveals the natural space that best describes the social landscape, which does not necessarily correspond to traditional categories. We illustrate the application of this framework in quadripolar and pentapolar real-world democratic processes, finding non-trivial ideological structures with clear connections to the underlying social context. Our methodology offers a comprehensive perspective of multilateral social tensions, as it incorporates complementary aspects of polarization: network segregation, opinion extremeness, and issue alignment.

physics.soc-ph↗