Evolution of migration trajectories and transnational social networks over time: a study among sub-Saharan African migrants in Europe

Abstract Background The use of modern contraception has increased in much of sub-Saharan Africa (SSA). However, the extent to which changes have occurred across the wealth spectrum among adolescents is not well known. We examine poor-rich gaps in demand for family planning satisfied by modern methods (DFPSm) among sexually active adolescent girls and young women (AGYW) using data from national household surveys. Methods We used recent Demographic and Health Surveys and Multiple Indicator Cluster Surveys to describe levels of wealth-related inequalities in DFPSm among sexually active AGYW using an asset index as an indicator of wealth. Further, we used data from countries with more than one survey conducted from 2000 to assess DFPSm trends. We fitted linear models to estimate annual average rate of change (AARC) by country. We fitted random effects regression models to estimate regional AARC in DFPSm. All analysis were stratified by marital status. Results Overall, there was significant wealth-related disparities in DFPSm in West Africa only (17.8 percentage points (pp)) among married AGYW. The disparities were significant in 5 out of 10 countries in Eastern, 2 out of 6 in Central, and 7 out of 12 in West among married AGYW and in 2 out of 6 in Central and 2 out of 9 in West Africa among unmarried AGYW. Overall, DFPSm among married AGYW increased over time in both poorest (AARC = 1.6%, p < 0.001) and richest (AARC = 1.4%, p < 0.001) households and among unmarried AGYW from poorest households (AARC = 0.8%, p = 0.045). DPFSm increased over time among married and unmarried AGYW from poorest households in Eastern (AARC = 2.4%, p < 0.001) and Southern sub-regions (AARC = 2.1%, p = 0.030) respectively. Rwanda and Liberia had the largest increases in DPFSm among married AGYW from poorest (AARC = 5.2%, p < 0.001) and richest (AARC = 5.3%, p < 0.001) households respectively. There were decreasing DFPSm trends among both married (AARC = − 1.7%, p < 0.001) and unmarried (AARC = − 4.7%, p < 0.001) AGYW from poorest households in Mozambique. Conclusion Despite rapid improvements in DFPSm among married AGYW from the poorest households in many SSA countries there have been only modest reductions in wealth-related inequalities. Significant inequalities remain, especially among married AGYW. DFPSm stalled in most sub-regions among unmarried AGYW.

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An Exploratory Study of COVID-19 Information on Twitter in the Greater Region

Big Data and Cognitive Computing ◽

10.3390/bdcc5010005 ◽

2021 ◽

Vol 5 (1) ◽

pp. 5

Author(s):

Ninghan Chen ◽

Zhiqiang Zhong ◽

Jun Pang

Keyword(s):

Machine Learning ◽

Social Networks ◽

Online Social Networks ◽

Exploratory Study ◽

Representation Learning ◽

Data Driven ◽

Learning Methods ◽

Twitter Users ◽

Over Time

The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out how Twitter users in the Greater Region (GR) and related countries react differently over time through conducting a data-driven exploratory study of COVID-19 information using machine learning and representation learning methods. We find that tweet volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 22 January 2020 to 5 June 2020, figuring out the main differences between GR and related countries.

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Contrasting Monetary and Multidimensional Poverty Measures in a Low-Income Sub-Saharan African Country

Social Indicators Research ◽

10.1007/s11205-020-02382-z ◽

2020 ◽

Vol 151 (2) ◽

pp. 547-574 ◽

Cited By ~ 1

Author(s):

Lukas Salecker ◽

Anar K. Ahmadov ◽

Leyla Karimli

Keyword(s):

Risk Factors ◽

Low Income ◽

Multidimensional Poverty ◽

Poverty Measurement ◽

Sub Saharan Africa ◽

Analytical Strategy ◽

Poverty Risk ◽

Two Measures ◽

Sub Saharan ◽

Over Time

AbstractDespite significant progress in poverty measurement, few studies have undertaken an in-depth comparison of monetary and multidimensional measures in the context of low-income countries and fewer still in Sub-Saharan Africa. Yet the differences can be particularly consequential in these settings. We address this gap by applying a distinct analytical strategy to the case of Rwanda. Using data from two waves of the Rwandan Integrated Household Living Conditions Survey, we combine comparing poverty rates cross-sectionally and over time, examining the overlaps and differences in the two measures, investigating poverty rates within population sub-groups, and estimating several statistical models to assess the differences between the two measures in identifying poverty risk factors. We find that using a monetary measure alone does not capture high incidence of multidimensional poverty in both waves, that it is possible to be multidimensional poor without being monetary poor, and that using a monetary measure alone overlooks significant change in multidimensional poverty over time. The two measures also differ in which poverty risk factors they put emphasis on. Relying only on monetary measures in low-income sub-Saharan Africa can send inaccurate signals to policymakers regarding the optimal design of social policies as well as monitoring their effectiveness.

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Transnational social fields in forced immobility: relations of young Sub-Saharan African migrants in Morocco with their families and friends

Identities ◽

10.1080/1070289x.2015.1024123 ◽

2015 ◽

Vol 23 (4) ◽

pp. 407-421 ◽

Cited By ~ 5

Author(s):

Inka Stock

Keyword(s):

African Migrants ◽

Social Fields ◽

Transnational Social Fields ◽

Sub Saharan

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Obesity and type 2 diabetes in sub-Saharan Africans – Is the burden in today’s Africa similar to African migrants in Europe? The RODAM study

BMC Medicine ◽

10.1186/s12916-016-0709-0 ◽

2016 ◽

Vol 14 (1) ◽

Cited By ~ 71

Author(s):

Charles Agyemang ◽

Karlijn Meeks ◽

Erik Beune ◽

Ellis Owusu-Dabo ◽

Frank P. Mockenhaupt ◽

...

Keyword(s):

Type 2 Diabetes ◽

African Migrants ◽

Sub Saharan ◽

Rodam Study

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Cracks in the Network Conversion Paradigm

International Journal for the Study of New Religions ◽

10.1558/ijsnr.v3i2.143 ◽

2012 ◽

Vol 3 (2) ◽

pp. 143-162 ◽

Cited By ~ 3

Author(s):

James Lewis

Keyword(s):

Social Networks ◽

Change Over Time ◽

New Religions ◽

Dominant Point ◽

Recruitment Patterns ◽

Over Time

One of the standard generalizations about new religions is that people convert to NRMs primarily through preexisting social networks. The present paper examines data on a variety of new religions which demonstrates that social networks are not always the dominant point of contact for new converts. Additionally, recruitment patterns change over time so that different factors become dominant at different points in a movement’s development. Two reasons why this variability has escaped the attention of most researchers is an unconscious tendency to assume that the sociological profiles of members of different NRMs are essentially similar, and the fact that such groups are typically studied synchronically rather than diachronically.

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Temporal Activity Path Based Character Correction in Heterogeneous Social Networks via Multimedia Sources

Advances in Multimedia ◽

10.1155/2018/2058670 ◽

2018 ◽

Vol 2018 ◽

pp. 1-16

Author(s):

Jun Long ◽

Lei Zhu ◽

Zhan Yang ◽

Chengyuan Zhang ◽

Xinpan Yuan

Keyword(s):

Social Networks ◽

Social Network ◽

Large Scale ◽

Multimedia Data ◽

Attribute Information ◽

Novel Method ◽

Relationship Network ◽

Heterogeneous Social Networks ◽

The Relationship ◽

Over Time

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.

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Quantifying Virality of Information in Online Social Networks

International Journal of Virtual Communities and Social Networking ◽

10.4018/jvcsn.2012010103 ◽

2012 ◽

Vol 4 (1) ◽

pp. 32-45 ◽

Cited By ~ 1

Author(s):

Abhishek Vaish ◽

Rajiv Krishna G. ◽

Akshay Saxena ◽

Dharmaprakash M. ◽

Utkarsh Goel

Keyword(s):

Social Networks ◽

Social Network ◽

Online Social Networks ◽

Online Social Network ◽

Critical Factors ◽

Asset Valuation ◽

Valuation Technique ◽

Information Item ◽

Viral Nature ◽

Over Time

The aim of this research is to propose a model through which the viral nature of an information item in an online social network can be quantified. Further, the authors propose an alternate technique for information asset valuation by accommodating virality in it which not only complements the existing valuation system, but also improves the accuracy of the results. They use a popularly available YouTube dataset to collect attributes and measure critical factors such as share-count, appreciation, user rating, controversiality, and comment rate. These variables are used with a proposed formula to obtain viral index of each video on a given date. The authors then identify a conventional and a hybrid asset valuation technique to demonstrate how virality can fit in to provide accurate results.The research demonstrates the dependency of virality on critical social network factors. With the help of a second dataset acquired, the authors determine the pattern virality of an information item takes over time.

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