scholarly journals Quantifying the differences in call detail records

2021 ◽  
Vol 8 (6) ◽  
pp. 201443
Author(s):  
Federico Botta
Keyword(s):  
Mobile Phone ◽  
Computational Social Science ◽  
Text Messages ◽  
Mobile Phone Data ◽  
Data Usage ◽  
Phone Calls ◽  
Different Types ◽  
Changes Over Time ◽  
The Relationship ◽  
Call Detail Records

The increasing availability of mobile phone data has attracted the attention of several researchers interested in studying our collective behaviour. Our interactions with the phone network can take several forms, from SMS messages to phone calls and data usage. Typically, mobile phone data are released to researchers in the form of call detail records , which contain records of different types of interactions, and can be used to analyse various aspects of our behaviour. However, the inherently behavioural nature of these interactions may result in differences between how we make phone calls and receive text messages. Studies which rely on data derived from these interactions, therefore, need to carefully consider these differences. Here, we aim to investigate differences and limitations of different types of mobile phone interactions data by analysing a large mobile phone dataset. We study the relationship between different types of interactions and show how it changes over time. We anticipate our findings to be of interest to all researchers working in the area of computational social science.

Mobile Phone Tower Tracking

2020 ◽  
Author(s):  
Anne Hardy
Keyword(s):  
Mobile Phone ◽  
Travel Behaviour ◽  
Text Messages ◽  
Phone Call ◽  
Mobile Phone Data ◽  
Data Sets ◽  
Travel Patterns ◽  
Mobile Phone Use ◽  
Time Space ◽  
Call Detail Records

Tracking tourists using mobile phone data involves collating mobile phone call detail records (CDR), that can determine travel patterns of mobile phone users. The size of the data involved in this style of research is enormous; Xiao, Wang, and Fang (2019) received 600 – 800 million records per day when they used mobile phone data from Shanghai, resulting in over 10 billion mobile phone trajectories. However, mobile phone data does not provide precise travel itineraries. Rather, the data is a series of time-space points, showing where mobile phone users were when they made or received calls or text messages. Inferences are required to determine which mobile phone users are tourists, and when they entered countries or regions. However, the ubiquity of mobile phone use and the size of the data sets available to researchers means that this form of data can be used as a proxy for accommodation and visitation (Xiao, Wang, and Fang, 2019; Ahas et al., 2008; Ahas et al., 2007). Many significant findings regarding travel behaviour have emerged from this technique, including understandings of the impacts of seasonality, the impacts of nationality, and the impacts of events. This chapter will review these findings as well as the challenges that arise from the use of this data.

scholarly journals SOCIAL NETWORK SIZE AND FREQUENCY OF ELECTRONIC COMMUNICATION: THE RELATIONSHIP TO INTERPERSONAL STRESS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S174-S174
Author(s):  
Xin Yao Lin ◽  
Margie E Lachman
Keyword(s):  
Social Network ◽  
Network Size ◽  
Text Messages ◽  
Interpersonal Stress ◽  
Electronic Communications ◽  
Daily Diary Study ◽  
Social Network Size ◽  
Phone Calls ◽  
Video Chat ◽  
The Relationship

Abstract Social relationships are beneficial for psychological wellbeing, but they are also associated with interpersonal stress. With the growing usage of multiple forms of electronic communications (EC) including phone calls, text messages, video chat, and internet among adults of all ages, it was of interest to explore the relationship between social network size (SNS), in-person communication (PC), and EC, and whether the relationship between SNS and frequency of communication is associated with interpersonal stress. A daily diary study was conducted over seven days for 142 participants ages 22 to 94. SNS was assessed with the social convoy model. Frequency of PC and EC, along with interpersonal stress, were assessed daily. As expected, multiple regression analysis results showed that older adults had smaller SNS and less frequent technology communication (text messages, video chat, internet) compared to younger adults. With regard to effects on interpersonal stress, there were no main effects for frequency of PC, EC, or SNS. However, the frequency of EC moderated the relationship between SNS and interpersonal stress, controlling for amount of PC. Among those with a smaller SNS, having more frequent EC was associated with less interpersonal stress compared to those with less frequent EC. For those with a larger SNS, having more frequent EC was associated with more interpersonal stress compared to those with less EC, but PC was not related to interpersonal stress. The discussion will consider implications of the findings for developing interventions to minimize stress from interpersonal communications, especially those that involve EC.

scholarly journals Preliminary needs assessment of mobile technology use for healthcare among homeless veterans

2014 ◽  
Author(s):  
D Keith McInnes ◽  
Gemmae M Fix ◽  
Jeffrey L Solomon ◽  
Beth Ann Petrakis ◽  
Leon Sawh ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Technology Use ◽  
Text Messaging ◽  
Text Messages ◽  
It Use ◽  
Homeless Veterans ◽  
Healthcare Needs ◽  
Phone Calls ◽  
Health Related

BACKGROUND: Homeless veterans have complex healthcare needs, but experience many barriers to treatment engagement. While information technologies (IT), especially mobile phones, are used to engage patients in care, little is known about homeless veterans’ IT use. This study examines homeless veterans’ access to and use of IT, attitudes toward health-related IT use, and barriers to IT in the context of homelessness. METHODS: Qualitative interviews were conducted with 30 homeless veterans in different housing programs in Boston, MA. Inductive thematic analysis was used. RESULTS: Most participants (90%) had a mobile phone and were receptive to IT use for health-related communications. A common difficulty communicating with providers was the lack of a stable mailing address. Some participants were using mobile phones to stay in touch with providers. Participants felt mobile-phone calls or text messages could be used to remind patients of appointments, prescription refills, medication taking, and returning for laboratory results. Mobile phone text messaging was seen as convenient, helped participants stay organized because necessary information was saved in text messages. Some reported concerns about the costs associated with mobile phone use (calls and texting), the potential to be annoyed by too many text messages, and not knowing how to use text messaging. CONCLUSION: Homeless veterans use IT and welcome its use for health-related purposes. Technology-assisted outreach among this population may lead to improved engagement in care.

scholarly journals College Student Problematic Internet Use and Digital Communication Medium Used With Parents: Cross-Sectional Study

10.2196/17165 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e17165
Author(s):  
Bradley Kerr ◽  
Jon D D'Angelo ◽  
Ali Diaz-Caballero ◽  
Megan A Moreno
Keyword(s):  
College Students ◽  
College Student ◽  
Internet Use ◽  
Protective Factor ◽  
Digital Communication ◽  
Text Messages ◽  
Problematic Internet Use ◽  
Phone Calls ◽  
Communication Frequency ◽  
The Relationship

Background Problematic internet use (PIU) is associated with mental health concerns such as depression and affects more than 12% of young adults. Few studies have explored potential influences of parent–college student digital communication on college students’ risk of PIU. Objective This study sought to understand the relationship between parent–college student digital communication frequency via phone calls, text messages, and Facebook contacts and PIU among college students. Methods Incoming first-year students were randomly selected from registrar lists of a midwestern and northwestern university for a 5-year longitudinal study. Data from interviews conducted in summer 2014 were used. Measures included participants’ daily Facebook visits, communication frequency with parents via phone call and text message, and 3 variables related to Facebook connection status and communication: (1) parent–college student Facebook friendship status, (2) college student blocking personal Facebook content from parent, and (3) Facebook communication frequency. PIU risk was assessed using the Problematic and Risky Internet Use Screening Scale. Analysis included participants who reported visiting Facebook at least once per day. Multiple linear regression was used, followed by a post hoc mediation with Hayes process macro to further investigate predictive relationships among significant variables. Results A total of 151 participants reported daily Facebook use and were included in analyses. Among these participants, 59.6% (90/151) were female, 62.3% (94/151) were from the midwestern university, and 78.8% (119/151) were white. Mean Facebook visits per day was 4.3 (SD 3.34). There was a collective significant effect between participant daily Facebook visits, college student–parent phone calls, texts, and all 3 Facebook connection variables (F6,144=2.60, P=.02, R2=.10). Phone calls, text messages, and Facebook contacts were not associated with PIU risk. However, two individual items were significant predictors for PIU: participant daily Facebook visits were positively associated with increased PIU risk (b=0.04, P=.006) and being friends with a parent on Facebook was negatively associated with PIU risk (b=–0.66, P=.008). Participant daily Facebook visits were not a significant mediator of the relationship between college student–parent Facebook friendship and PIU risk (b=–0.04; 95% CI –0.11 to 0.04). Conclusions This study did not find support for a relationship between parent–college student digital communication frequency and PIU among college students. Instead, results suggested Facebook friendship may be a protective factor. Future studies should examine how a parent-child Facebook friendship might protect against PIU among children at varying developmental stages.

scholarly journals Changes Over Time and Predictors of Online Gambling in Three Norwegian Population Studies 2013–2019

2021 ◽  
Vol 12 ◽  
Author(s):  
Ståle Pallesen ◽  
Rune Aune Mentzoni ◽  
Arne Magnus Morken ◽  
Jonny Engebø ◽  
Puneet Kaur ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Video Game ◽  
Online Gambling ◽  
Mobile Phone Data ◽  
Video Gaming ◽  
Gambling Problems ◽  
Cross Sectional ◽  
Norwegian Population ◽  
Changes Over Time ◽  
Over Time

Objectives: To investigate changes over time and identify predictors of online gambling among gamblers by using three Norwegian representative samples covering a 6-year (2013–2019) period. We also aimed to identify different characteristics (including video game participation and video gaming problems) of online compared to offline gamblers.Methods: Data from gamblers (N = 15,096) participating in three cross-sectional surveys (2013, 2015, and 2019) based on random sampling from the Norwegian Population Registry were analyzed. Participants were asked how frequently they engaged in online gambling on different platforms (e.g., mobile phone). Data on sociodemographics, games gambled, gambling problems, gaming, and problem gaming were collected and analyzed by logistic regression analyses.Results: Overall, an increase in online gambling from 2013 to 2015 was found (a larger percentage of gamblers reported having gambled online at least once during the last year), and an increase in online gambling from 2015 to 2019 was found (more gamblers reported having gambled online at least once last year and at least once per week). The increase was largest for gambling on mobile phone. Consistent predictors of online gambling (at least once last year and at least once per week) were male gender, high income, being unemployed, being on disability pension, having work assessment allowance, being a homemaker or retiree, number of games gambled, and gambling problems.Conclusions: Online gambling, especially on mobile phones, has increased significantly during the last 6 years in Norway. Hence, gambling availability seems to have grown, which may pose a risk for development of gambling problems. Compared to offline gamblers, online gamblers were more likely to be men, young, not working or studying, gambling on several games, and having gambling problems. Responsible gambling efforts aiming at preventing or minimizing harm related to online gambling should thus target these groups.

scholarly journals Mobile Phone Indicators and Their Relation to the Socioeconomic Organisation of Cities

2019 ◽  
Vol 8 (1) ◽  
pp. 19 ◽  
Author(s):  
Clémentine Cottineau ◽  
Maarten Vanhoof
Keyword(s):  
Mobile Phone ◽  
Census Data ◽  
Social Science Research ◽  
Science Research ◽  
Computational Social Science ◽  
Mobile Phone Data ◽  
Spatial And Temporal Heterogeneity ◽  
Statistical Relationships ◽  
Socioeconomic Data ◽  
The City

Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities is increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by censuses. In this article we explore the convergence between mobile phone data and more traditional socioeconomic data from the national census in French cities. We extract mobile phone indicators from six months worth of Call Detail Records (CDR) data, while census and administrative data are used to characterize the socioeconomic organisation of French cities. We address various definitions of cities and investigate how they impact the statistical relationships between mobile phone indicators, such as the number of calls or the entropy of visited cell towers, and measures of economic organisation based on census data, such as the level of deprivation, inequality and segregation. Our findings show that some mobile phone indicators relate significantly with different socioeconomic organisation of cities. However, we show that relations are sensitive to the way cities are defined and delineated. In several cases, changing the city delineation rule can change the significance and even the sign of the correlation. In general, cities delineated in a restricted way (central cores only) exhibit traces of human activity which are less related to their socioeconomic organisation than cities delineated as metropolitan areas and dispersed urban regions.

scholarly journals Identifying Urban Residents’ Activity Space at Multiple Geographic Scales Using Mobile Phone Data

2020 ◽  
Vol 9 (4) ◽  
pp. 241
Author(s):  
Lunsheng Gong ◽  
Meihan Jin ◽  
Qiang Liu ◽  
Yongxi Gong ◽  
Yu Liu
Keyword(s):  
Built Environment ◽  
Mobile Phone ◽  
Human Life ◽  
Activity Space ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Activity Spaces ◽  
Point Of Interest ◽  
The Relationship

Residents’ activity space reflects multiple aspects of human life related to space, time, and type of activity. How to measure the activity space at multiple geographic scales remains a problem to be solved. Recently, the emergence of big data such as mobile phone data and point of interest data has brought access to massive geo-tagged datasets to identify human activity at multiple geographic scales and to explore the relationship with built environment. In this research, we propose a new method to measure three types of urban residents’ activity spaces—i.e., maintenance activity space, commuting activity space, and recreational activity space—using mobile phone data. The proposed method identifies the range of three types of residents’ activity space at multiple geographic scales and analyzing the relationship between the built environment and activity space. The research takes Zhuhai City as its case study and discovers the spatial patterns for three activity space types. The proposed method enables us to achieve a better understanding of the human activities of different kinds, as well as their relationships with the built environment.

scholarly journals Preliminary needs assessment of mobile technology use for healthcare among homeless veterans

2014 ◽  
Author(s):  
D Keith McInnes ◽  
Gemmae M Fix ◽  
Jeffrey L Solomon ◽  
Beth Ann Petrakis ◽  
Leon Sawh ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Technology Use ◽  
Text Messaging ◽  
Text Messages ◽  
It Use ◽  
Homeless Veterans ◽  
Healthcare Needs ◽  
Phone Calls ◽  
Health Related

BACKGROUND: Homeless veterans have complex healthcare needs, but experience many barriers to treatment engagement. While information technologies (IT), especially mobile phones, are used to engage patients in care, little is known about homeless veterans’ IT use. This study examines homeless veterans’ access to and use of IT, attitudes toward health-related IT use, and barriers to IT in the context of homelessness. METHODS: Qualitative interviews were conducted with 30 homeless veterans in different housing programs in Boston, MA. Inductive thematic analysis was used. RESULTS: Most participants (90%) had a mobile phone and were receptive to IT use for health-related communications. A common difficulty communicating with providers was the lack of a stable mailing address. Some participants were using mobile phones to stay in touch with providers. Participants felt mobile-phone calls or text messages could be used to remind patients of appointments, prescription refills, medication taking, and returning for laboratory results. Mobile phone text messaging was seen as convenient, helped participants stay organized because necessary information was saved in text messages. Some reported concerns about the costs associated with mobile phone use (calls and texting), the potential to be annoyed by too many text messages, and not knowing how to use text messaging. CONCLUSION: Homeless veterans use IT and welcome its use for health-related purposes. Technology-assisted outreach among this population may lead to improved engagement in care.

scholarly journals COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA

2016 ◽  
Vol XLI-B2 ◽  
pp. 471-476
Author(s):  
Rui Cao ◽  
Wei Tu ◽  
Jinzhou Cao ◽  
Qingquan Li
Keyword(s):  
Mobile Phone ◽  
Smart Card ◽  
Human Movement ◽  
Mobile Phone Data ◽  
Temporal Data ◽  
Human Movements ◽  
Smart Card Data ◽  
Long Time ◽  
Relationship Of ◽  
The Relationship

The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.

scholarly journals College Student Problematic Internet Use and Digital Communication Medium Used With Parents: Cross-Sectional Study (Preprint)

2019 ◽  
Author(s):  
Bradley Kerr ◽  
Jon D D'Angelo ◽  
Ali Diaz-Caballero ◽  
Megan A Moreno
Keyword(s):  
College Students ◽  
College Student ◽  
Internet Use ◽  
Protective Factor ◽  
Digital Communication ◽  
Text Messages ◽  
Problematic Internet Use ◽  
Phone Calls ◽  
Communication Frequency ◽  
The Relationship

BACKGROUND Problematic internet use (PIU) is associated with mental health concerns such as depression and affects more than 12% of young adults. Few studies have explored potential influences of parent–college student digital communication on college students’ risk of PIU. OBJECTIVE This study sought to understand the relationship between parent–college student digital communication frequency via phone calls, text messages, and Facebook contacts and PIU among college students. METHODS Incoming first-year students were randomly selected from registrar lists of a midwestern and northwestern university for a 5-year longitudinal study. Data from interviews conducted in summer 2014 were used. Measures included participants’ daily Facebook visits, communication frequency with parents via phone call and text message, and 3 variables related to Facebook connection status and communication: (1) parent–college student Facebook friendship status, (2) college student blocking personal Facebook content from parent, and (3) Facebook communication frequency. PIU risk was assessed using the Problematic and Risky Internet Use Screening Scale. Analysis included participants who reported visiting Facebook at least once per day. Multiple linear regression was used, followed by a post hoc mediation with Hayes process macro to further investigate predictive relationships among significant variables. RESULTS A total of 151 participants reported daily Facebook use and were included in analyses. Among these participants, 59.6% (90/151) were female, 62.3% (94/151) were from the midwestern university, and 78.8% (119/151) were white. Mean Facebook visits per day was 4.3 (SD 3.34). There was a collective significant effect between participant daily Facebook visits, college student–parent phone calls, texts, and all 3 Facebook connection variables (<i>F</i><sub>6,144</sub>=2.60, <i>P</i>=.02, <i>R</i><sup>2</sup>=.10). Phone calls, text messages, and Facebook contacts were not associated with PIU risk. However, two individual items were significant predictors for PIU: participant daily Facebook visits were positively associated with increased PIU risk (<i>b</i>=0.04, <i>P</i>=.006) and being friends with a parent on Facebook was negatively associated with PIU risk (<i>b</i>=–0.66, <i>P</i>=.008). Participant daily Facebook visits were not a significant mediator of the relationship between college student–parent Facebook friendship and PIU risk (<i>b</i>=–0.04; 95% CI –0.11 to 0.04). CONCLUSIONS This study did not find support for a relationship between parent–college student digital communication frequency and PIU among college students. Instead, results suggested Facebook friendship may be a protective factor. Future studies should examine how a parent-child Facebook friendship might protect against PIU among children at varying developmental stages.

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