- Regular article
- Open Access
Quantifying gender preferences in human social interactions using a large cellphone dataset
© The Author(s) 2019
- Received: 7 December 2017
- Accepted: 19 February 2019
- Published: 12 March 2019
In human relations individuals’ gender and age play a key role in the structures and dynamics of their social arrangements. In order to analyze the gender preferences of individuals in interaction with others at different stages of their lives we study a large mobile phone dataset. To do this we consider four fundamental gender-related caller and callee combinations of human interactions, namely male to male, male to female, female to male, and female to female, which together with age, kinship, and different levels of friendship give rise to a wide scope of human sociality. Here we analyse the relative strength of these four types of interaction using call detail records. Our analysis suggests strong age dependence for an individual of one gender choosing to call an individual of either gender. We observe a strong bonding with the opposite gender across most of their reproductive age. However, older women show a strong tendency to connect to another female that is one generation younger in a way that is suggestive of the grandmothering effect. We also find that the relative strength among the four possible interactions depends on phone call duration. For calls of medium and long duration, opposite gender interactions are significantly more probable than same gender interactions during the reproductive years, suggesting potential emotional exchange between spouses. By measuring the fraction of calls to other generations we find that mothers tend to make calls more to their daughters than to their sons, whereas fathers make calls more to their sons than to their daughters. For younger callers, most of their calls go to the same generation contacts, while older people call the younger people more frequently, which supports the suggestion that affection flows downward. Our study primarily rests on resolving the nature of interactions by examining the durations of calls. In addition, we analyse the intensity of the observed effects using a score based on a null model.
- Social networks
- Egocentric networks
- Mobile phones
- Life history
- Gender differences
- Sex differences
In social interactions between humans, gender and age play a key role in the communities and social structures they form and the dynamics therein. For the caller–callee interactions in mobile communication there are four fundamental possibilities, namely male to male, male to female, female to male, and female to female, which together with age, kinship, and different levels of friendships affect the strengths of social interactions, giving rise to a wide scope of human sociality. The studies of primate brain size and its relation to their average social group size suggest that humans are able to maintain of the order of 150 stable relationships (Dunbar number) [1–3]. In addition the Social Brain hypothesis suggests that on the basis of emotional closeness human social networks can be divided into four cumulative layers of 5, 15, 50 and 150 individuals, respectively . The concept of emotional closeness is, in general, hard to quantify, but previous studies have shown how it can be associated with the frequency of communication between two individuals [5, 6]. This makes the concept quantifiable such that one can observe how much an individual shares social resources with his or her contacts of different gender and age.
Over the past decade or so, much research on human communication patterns has been done by using “digital footprints” data from modern communication technologies such as mobile phone calls and text messages as well as social media like Facebook, and Twitter [7–9]. Of these the mobile phone communication data of call detail records (CDRs) has turned out to help us in getting insight into the structure and dynamics of social networks, human mobility and behavioural patterns in much finer details than before . It has also revealed how microscopic properties related to individuals translate to macroscopic features of their social organization such as networks. As a result of these studies we now have quite a good understanding of a number of structural properties of human social networks such as degree, strength, clustering coefficient, community structure, and motifs [10–12].
Apart from these basic structural properties of networks, more recent studies have given us insight into a number of other aspects of social networks, namely their dependence on temporal, geographic, demographic, and behavioral factors of individuals in the network [13–17]. One such observation pertains to the shifting patterns of human communication across the reproductive period of their lives, which appears to reflect parental care [18, 19]. Another is a study using the postal code information in the data to show that the tie strength is related to geographical distance . In addition, it has been shown that there is a universal pattern of time allocation to differently ranked social contacts . Finally, recent studies indicate variation in connections and the number of friends with the age and gender [22, 23]. The importance of the strength and significance of communication with top-ranked contacts have also been studied in detail [18, 22].
In the present study, we focus on measuring the relative strengths of the four possible pairwise caller–callee interactions over their lifespans as a function of the caller’s age. From the point of view of call initiation, we find that females play a more active role during their reproductive years as well as during their grandmothering period [24, 25]. The grandmothering hypothesis is usually studied in the context of human longevity and evolutionary benefits. The notion deals with the focus of post-menopausal on their grandchildren. In general, the social focus of women are known to shift from the opposite gender in the same age cohort, when they are young, to the age cohort of their children, as they grow older. We observe that while females of grandmothering age are found to give more attention to their children, males up to the age of 50 years still keep stronger connection with their spouses of slightly younger age. Furthermore, the fraction of calls to individuals of different generations indicates that mothers tend to call their daughters more than their sons, whereas fathers call their sons more than their daughters. For younger individuals, most of their calls go to contacts of the same generation, whereas older people call younger people more frequently. The calling activity of older adults with the younger individuals who are below or around their reproductive age would signify parental and alloparental care, that is, caring for the children of children. We group these kind of behaviour as affection flows downward.
In this study we analyse mobile phone communication records of a particular European mobile service provider containing time series of call detail records or CDRs of caller–callee pairs. This dataset also includes demographic information such as age and gender of the callers. By using the gender information we measure the relative strengths for the four basic calling pattern such that we count the total fraction of calls for the caller–callee pairs of the same or of different genders by assuming a cut-off for the minimum call duration. We analyse all the CDRs for the year 2007 on a month-by-month basis for more than 2.4 million subscribers where both the caller’s and the callee’s demographics are known, totaling over 30 million calls. Since datasets of this kind are susceptible to error due to multiple subscriptions, we filtered out customers who have multiple subscriptions under the same contract number. Our study based on CDRs allows obtaining anonymized data from a very large population, but is in contrast to small-scale studies where volunteers are recruited and cross-validation of results is possible by collecting information from the participants through questionnaires [21, 26].
In order to analyze the gender preferences of individuals in interaction with others at different stages of their lives we choose the age of the caller and count the total number of calls within a time window. We apply a threshold for minimum call duration, such that calls shorter than the threshold value are considered not to be indicative of emotional closeness while calls longer than that are taken to indicate a meaningful emotional or social exchange relationship between the caller and the callee. Then we calculate the relative probabilities for the four possible types of caller to callee interaction. As it is difficult to decide a priori where the borderline between meaningless and meaningful is, we will vary the threshold for minimum call duration in measuring how the probabilities of the four ways of interaction vary with age and gender of the callers.
The probabilities used in the null model that are used to calculate the normalized scores corresponding to the results in Fig. 2. The values shown below correspond to the age brackets used in Fig. 2. The probabilities for the different pairs are calculated using equations similar to Eq. (2) (for FF pairs)
In this study, we have measured the relative interaction probabilities for the four possible caller–callee pairs of the same and opposite gender. We have observed that in general the interaction probabilities are strongly dependent on the age and gender of the caller in relation to the age and gender of the callee. Also, we observed the communication over the generation gap as depicted in Fig. 1 showing the lobed structure and in the Appendix in Fig. 9, where we depict the distribution of calls made by the callers of certain age to callees as a function of callees’ age showing it to be bimodal [18, 19, 22].
Our findings from the study of the distributions of call duration for different age groups of the caller (Fig. 2) shows that the MF interactions tend to increase with call duration up to age 50 years, suggesting that men have a strong emotional connection with their opposite gender spouse of about the same age. In contrast, the FM interactions indicate that women are not as active after the age of 35 years, and have a decreasing trend for medium or long call duration with age. On the other hand, the MM interactions show initially greater probability for short call duration at younger ages, after which this becomes least probable for medium and higher call duration for any age of the caller. The FF interactions start with the lowest probability of all at younger ages, then shows a steadily increasing trend for medium and higher call duration with the age of the caller.
In the investigation of the relative probabilities for the four types of interaction as a function of the caller’s age with calls above certain threshold value (30 sec, 60 sec, 120 sec and 240 sec) (Fig. 3), we show that the FF interactions have an increasing trend with the caller’s age. This is due to frequent interactions between the daughter and her mother, an indication that the grandmothering effect has set in. An opposite trend is observed for the FM interactions, i.e. the relative probability shows a decreasing trend with age. On the other hand, the MF interactions show a high probability for ages ranging from 20 to 50 years. After that, it shows a decreasing trend up to the age of 55 years, and then beyond that again shows an increasing trend. The MM interaction curve shows the weakest interaction after the age of 25 years.
The effect of the difference in the number of male and female subscribers on the counting of pairs and the results shown in either of Fig. 2 and Fig. 3 is understood with the help of the scores calculated using the null model. These scores reveal how the populations of males and females influence the counting of pairs. Moreover, zero being a reference for the score, the latter is able to differentiate between contrasting cases, that is between negative (below the expectation with respect to the null model) and positive scores (above the expectation). For example, in Fig. 6(A) that corresponds to Fig. 2, scores for female-female calling are found to change from negative to positive with age of the caller. Overall, the scores lend support to our original results yet bringing clarity on the nature of the results.
Looking at the fractions of calls of duration more than 100 sec as a function of the caller’s age (Fig. 4) revealed that for the FF interactions there is an increase from 50 to 60 years of age, which once again is taken as a clear evidence of grandmothering setting in. We have also found that on the basis of the average call duration that around 35 years of age the duration of female-to-female calls is highest among the four possible types of interaction. This can again be interpreted as a signature for the grandmothering effect. Furthermore, we showed (Fig. 5) that there is a fraction of total calls going from callers to callees who are either one generation older or one generation younger. Here we observed that for female callers the fraction of calls going to a different generation is, for all ages, always greater than for male callers. More precisely, the FF interactions show the highest probability, most likely reflecting strong ties between mothers and their daughters. On the other hand, at a younger age, a large fraction of calls go from males to females, suggesting that sons are strongly attached to their mothers before marriage. After the age of 40 years, the MF and FM interaction curves are very close to each other, suggesting that sons get the same amount of attention from both parents. More generally, we have found that younger callers, most of the calls (70–90%) to callees of the same generation. On the other hand, for older people, most of their calls go to their children (i.e. contacts who are younger by a generation), which supports the claim that affection flows downward. Broadly speaking, our conclusions regarding the preference of communicating individuals as a function of their age, and in particular, the preference of women in their post-reproductive period, is based on the observed variation in the quantities, namely the relative frequency of outgoing calls, the propensity to make calls of longer duration, and the proliferation of cross-generational calls. However, the consistency with alternative hypotheses could as well be investigated but those should be able to explain the patterns of communication taking into account the age dependent variation in kinship and different levels of friendship.
The advent of newer channels of digital communication in the last decade has rapidly supplemented the usage of mobile phones. The pattern of communication availing multiple modes, for example, voice calling in conjunction with text-messaging or through social networking services, is in turn able to characterize the nature of sociality [32–34]. However, the fact that variability in calls can also serve as an important factor, has been rather overlooked. In previous works by some of the authors we had focussed on undirected communication and tried distinguishing communication between peers, partners and kins for individuals of different gender and age . Here, we investigate outgoing calls specific to gender and age, and consider duration of calls in the same spirit as multiple available channels. On one hand the current study stands consistent with the earlier works that revealed patterns in sociality like grandmothering, on the other the study might be indicative of gender and age differences in selecting different channels of communication. The understanding of the immediate social neighbourhood of individuals as well as the preferences in the style of communication would be valuable inputs to the developing fields of mobile health and medicine [35, 36].
A.G. and K.K. acknowledge support from project COSDYN, Academy of Finland (Project no. 276439). K.B., D.M. and K.K. acknowledge support from H2020 EU project IBSEN. D.M. acknowledge to CONACYT, Mexico for supporting grant 383907. RD’s research is supported by an ERC Advanced Investigator award.
Availability of data and materials
The datasets analysed during the current study are not publicly available due to a signed non-disclosure agreement. The dataset contains sensitive information of the subscribers, particularly age, gender, postal address and the location of the most accessed cell tower.
This work was supported by the Academy of Finland Research project (COSDYN) No. 276439 (AG and KK), EU HORIZON 2020 FET Open RIA project (IBSEN) No. 662725 (KB, DM, KK), the CONACYT (Mexico) grant No. 383907 (DM), and ERC Advanced Investigator Award (RD).
Conceptualization: AG, DM, KB; methodology: All authors; formal analysis: AG; resources: KK; data curation: DM; writing (original draft preparation): AG, KB, RD; writing (review and editing): All authors; visualization: AG; supervision: RD, KK; funding acquisition: RD, KK. All authors gave final approval for publication.
The authors declare that they have no competing interests.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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