Telephone communication patterns in Austria: A comparison of the IPFP-based graph-theoretic and the intramax approaches (original) (raw)
Related papers
1992
The explosion of activities and requirements associated with the production, processing and transfer of information is increasingly being matched by a profileration and diversification of new telecommunication media for transmitting information, including text processing and transmission services such as facsimile transmission, videotex, teleconference services, electronic mail etc. Nevertheless, the telephone is still - by far - the most important telecommunication service. The paper results from ESF-research undertaken within the Network on European Communication and Transport Activity Research (NECTAR) and relates to telephone communication undertaken for the Netherlands by Rietveld and Jansen (1990) and Switzerland by Rossera (1990). The current study focuses on the Austrian case and relies on data measured by the Austrian PTT in 1991, in terms of erlangs, an internationally widely used and reliable measure of telecommunication contact intensity. The data refer to the total tele...
A comparative analysis of the statistical properties of large mobile phone calling networks
Scientific Reports, 2014
If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.
2017
Is a temporal landline phone call network graph series led by the presence of small world phenomenon? Are order and average vertex degree of the network graphs associated to small – world – ness? How are related size and order of the network graphs in this temporal series? A continuously graded notion of small – world – ness is used to study the presence of small world phenomenon. Spearman’s and Kendall’s correlation coefficients are used to perform a non – parametric correlation analysis between small – world – ness and order/average vertex degree. Linear regression on log – transformed quantities is used to analyse the relationship between size and order. It is achieved by the study that, the presence of small – world – ness is confirmed in each time step of the series, and there is no significant association between small – world – ness and graph order/average vertex degree. A significant positive power relationship between size and order is found.
Descriptive Analysis of Characteristics: A Case Study of a Phone Call Network Graph
2016 UBT International Conference
Nowadays, systematic collection of data has necessitated a detailed statistical analysis as a necessary tool to make a mathematical characterization of them with the purpose of gathering information about the present or the future. Our aim in this paper is to analyze a landline phone call network graph from the perspective of descriptive analysis. We explore the characteristics and structural properties of the network graph constructed using an anonymous collection of data gathered from a Call Data Records of a telecommunication operator center located in south of Albania. The R statistical computing platform is used for network graph analysis.
On the structural properties of massive telecom call graphs: findings and implications
2006
With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.
New Journal of Physics, 2014
Big data open up unprecedented opportunities to investigate complex systems including the society. In particular, communication data serve as major sources for computational social sciences but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. By using the filtered networks we investigated the statistics and temporal evolution of small directed 3-motifs and conclude that closed communication triads have a formation time-scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve to other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.
Innovative Computing and Communications. ICICC 2024. Lecture Notes in Networks and Systems, vol 1038. Springer, Singapore., 2024
This research analyzes landline telecommunication patterns by examining call records from a southern Albanian operator across two non-consecutive months. Through cross-sectional analysis, rigorous data filtration, and aggregation, it utilizes statistical techniques such as descriptive statistics, normality tests (Shapiro-Wilk, Anderson-Darling), and the Mann-Whitney U test, along with Pearson’s correlation and visual tools (scatter, time-series plots, heatmaps), to show daily and hourly call trends. The main conclusions present distinct call duration and start time patterns. There is considerable variability, and a significant positive linear relationship between day-to-day changes in daily call volume and daily call duration in both months. Periods of heightened activity were identified during the mornings, late afternoon hours, and weekends. These underscore the complex nature of telecommunications interactions. The research findings improve understanding and network optimization strategies and also highlight the necessity for dynamic, data-centric approaches. The adoption of advanced analytical methods, including artificial intelligence, is supported to augment operational efficiency, shaping the telecommunications sector’s advancement toward a more adaptive, knowledge-based future.
On the structural properties of massive telecom call graphs
Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06, 2006
With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.
Analysing Ireland's Interurban Communication Network using Call Data Records
IET Irish Signals and Systems Conference (ISSC 2012), 2012
This work utilises data from an Irish mobile phone network to provide a preliminary, but novel, analysis of the interurban communication network between twenty five of the largest cities and towns in Ireland. An intuitive technique is applied to a mobile phone operator's call detail records to identify the actual subscriber population of different urban areas with various penetration rates. Weighted communication links are generated between the urban centres based on spatial and temporal metrics of distance, and are examined for different times of the day and for different days of the week. These communication links are compared to the output of a standard gravity model in order to ascertain the latter's ability to accurately represent Ireland's interurban communication network. The results obtained are presented and discussed within.