The Experts below are selected from a list of 5328 Experts worldwide ranked by ideXlab platform
R I M Dunbar - One of the best experts on this subject based on the ideXlab platform.
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use of Social Network sites and instant messaging does not lead to increased Offline Social Network size or to emotionally closer relationships with Offline Network members
Cyberpsychology Behavior and Social Networking, 2011Co-Authors: Thomas V Pollet, Sam G B Roberts, R I M DunbarAbstract:The effect of Internet use on Social relationships is still a matter of intense debate. This study examined the relationships between use of Social media (instant messaging and Social Network sites), Network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using Social media was associated with a larger number of online Social Network "friends." However, time spent using Social media was not associated with larger Offline Networks, or feeling emotionally closer to Offline Network members. Further, those that used Social media, as compared to non-users of Social media, did not have larger Offline Networks, and were not emotionally closer to Offline Network members. These results highlight the importance of considering potential time and cognitive constraints on Offline Social Networks when examining the impact of Social media use on Social relationships.
Munongo Shallone - One of the best experts on this subject based on the ideXlab platform.
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Social media and mobile money adoption: comparative evidence from South Africa and Zimbabwe
2019Co-Authors: Munongo ShalloneAbstract:Abstracts in English, Afrikaans and ZuluThe study investigated the effects of Social media on mobile money adoption in South Africa and Zimbabwe. The main gap identified in empirical literature is the omission of Social media use in technology adoption models and Social Networking theories. While some theories acknowledge the role of Social influences in technology adoption, the Social interactions considered therein are not mediated through the internet as is Social media. Furthermore, no empirical study has to date focused on how Social media influences mobile money technology adoption. Thus, this study deviates from the Offline Social Network analysis approach which is restricted to the neighbourhood effects, physical contact, cell phone calls and text messages where information on mobile money technology is disseminated to an individual’s limited Social circle. The secondary data used for the study were obtained from individual responses in the cross-sectional FinScope consumer surveys South Africa 2015 and Zimbabwe 2014 which were conducted and reported by FinMark Trust (2015; 2014). The study employed the binary logistic regression model to estimate the nature of effect. The results of the study indicated that use of Social media had a positive and statistically significant impact on mobile money adoption in both South Africa and Zimbabwe. The results also revealed that despite there being a lower internet penetration and Social media usage rate in Zimbabwe than South Africa, the use of Social media in the former led to a higher rate of mobile money adoption. The study also established that mere use of Social media and availability of mobile money technology did not translate to a high adoption rate; instead, availability had to be matched by a demand for the financial services. Additionally, the study found that the interaction of mobile money adoption and use of Social media increased the overall mobile money adoption in both countries. The study recommended the implementation of collective policies that increase internet penetration to facilitate increased use of Social media platforms and promote mobile money adoption to foster improved financial inclusion in developing countries.Hierdie studie het die gevolge van sosiale media op die ingebruikneming van mobiele geld in Suid-Afrika en Zimbabwe ondersoek. Die belangrikste leemte wat in empiriese literatuur geïdentifiseer is, is die weglating van die gebruik van sosiale media in tegnologieaanvaardingsmodelle en sosialenetwerkvorming-teorieë. Hoewel sommige teorieë (teorie van beredeneerde handeling; teorie van beplande gedrag; diffusie van innovasie) die rol van sosiale invloede op tegnologieaanvaarding erken, word die sosiale interaksies wat daarin oorweeg word nie deur middel van die internet bemiddel nie, soos wel in die geval van sosiale media. Boonop het geen empiriese studie tot op hede gefokus op hoe sosiale media die ingebruikneming van mobielegeld-tegnologie beïnvloed nie. Hierdie studie wyk dus af van die niegekoppelde sosialenetwerkontleding-benadering, wat beperk is tot die omgewingsgevolge, fisieke kontak, selfoonoproepe en teksboodskappe, waar inligting oor mobielegeld-tegnologie aan ʼn individu se beperkte sosiale kring versprei word. Die sekondêre data wat vir die studie gebruik is, is verkry uit afsonderlike response in die deursnee- FinScope-verbruikersopnames (Suid-Afrika 2015 en Zimbabwe 2014), wat onderneem en bekendgemaak is deur FinMark Trust (2015; 2014). Die studie maak gebruik van die binêre logistiese regressiemodel om die aard van effek te skat. Studiebevindings dui daarop dat die gebruik van sosiale media ’n positiewe en statisties beduidende uitwerking op die ingebruikneming van mobiele geld in sowel Suid-Afrika as Zimbabwe het. Die resultate wys ook dat, ondanks ’n laer internetpenetrasie en sosialemedia-gebruikskoers in Zimbabwe, die gebruik van sosiale media in Zimbabwe tot ’n hoër koers van ingebruikneming van mobiele geld in dié land as in Suid-Afrika tot gevolg het. Daar word verder waargeneem dat die blote gebruik van sosiale media en die beskikbaarheid van mobielegeld-tegnologie nie geredelik omgesit kan word in ’n hoë ingebruiknemingskoers nie; beskikbaarheid moet met ’n vraag na die finansiële dienste gepaard gaan. Daarbenewens toon die studie dat die interaksie tussen mobielegeld-ingebruikneming en die gebruik van sosiale media die oorkoepelende ingebruikneming van mobiele geld in albei lande versterk. Die studie beveel die implementering van beleide aan wat internetpenetrasie verhoog om wydverspreide gebruik van sosiale media te fasiliteer, wat op sy beurt die ingebruikneming van mobiele geld sal bevorder, wat finansiële insluiting sal bevorder.Ucwaningo luphenyisise imiphumela ye-Social media ekwamukelweni kwe-mobile money eNingizimu Afrika naseZimbabwe. Igebe elikhulu eliphawuliwe kwimibhalo yobufakazi ukweqiwa kokussetshenziswa kwe-Social media ekwamukelweni kwama-technology adoption models kanye namathiyori e-Social Networking. Kodwa amanye amathiyori (i-theory of reasoned action; i-theory of planned behaviour; i-diffusion of innovation) amukela indima yemithelela ye-Social influences ekwamukelweni kwetheknoloji, ngokusebenzisana kwama-Social interactions abonelelwe lapha, awaxhunyaniswa nge-inthanethi, njenge-Social media. Kanti-ke futhi okunye, akukho bufakazi bocwaningo kuze kubemanje obugxile kwindlela i-Social media enomthelela ngayo kwi-mobile money technology adoption. Ngakho-ke, lolu cwaningo luyehluka kwizinqubo ze-Offline Social Network analysis approach, enezihibe kwimiphumela esondelene nayo, ukuxhumana ngokubamba, ukushayelana izingcingo nge-cellphone, kanye nemilayezo ebhaliwe, lapho ulwazi kwi-mobile money technology lusatshalaliswa kumuntu ngamunye nalabo asondelene nabo. I-secondary data esetshenzisiwe kucwaningo itholakale kwizimpendulo zabantu ngamunye kwi-cross-sectional FinScope consumer surveys (iNingizimu Afrika 2015 kanye neZimbabwe 2014), olwenziwa nokubikwa nge-FinMark Trust (2015:2014). Ucwaningo lusebenzisa i-binary logistic regression model ukulinganisa inhlobo yomphumela. Imiphumela yocwaningo ikhombisa ukuthi i-Social media inomphumela omuhle futhi ngomphumela wezibalo ezibalulekile ekwamukelweni kwe-mobile money okwamukelwe kuwo womabili amazwe iNingizimu Afrika kanye neZimbabwe. Imiphumela ikhombise nokuthi, ngisho noma i-inthanethi ingakangeneleli kangako kwezinye izindawo, kodwa izinga lokusetshenziswa kwe-Social media eZimbabwe kungaphezulu kuneNingizimu Afrika, ukusetshenziswa eZimbabwe kuhola phambili ngezinga eliphezulu ekwamukelweni kwe-mobile money kunaseNingizimu Afrika. Kanti futhi kuphawulwa ukuthi ukusetshenziswa kwe-Social media kanye nokutholakala kwe-mobile money technology, akuhambelani ngezinga lokwamukelwa kakhulu; ukutholakala kumele kuhambelane nesidingeko samasevisi ezezimali. Nangaphezu kwalokho, ucwaningo lukhombisa ukuthi ukusebenzisana kokwamukelwa kwe-mobile money nokusetshenziswa kwe-Social media kuphakamisa ukwamukelwa kakhulu kwe-mobile money kuwo womabili amazwe. Ucwaningo luncoma ukuthi ukwamukelwa kwemigomo enyusa ukungenelela kakhulu kwe-inthanethi ukulekelela ukusetshenziswa kakhulu kwe-Social media, kanti futhi lokhu okuzophakamisa kakhulu ukwamukelwa kwe-mobile money okusiza ukubandakanya wonke kwezezimali.Business ManagementD. Phil. (Management Sciences
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Social media and mobile money adoption: comparative evidence from South Africa and Zimbabwe
2019Co-Authors: Munongo ShalloneAbstract:Abstract in English, Afrikaans and ZuluThe study investigated the effects of Social media on mobile money adoption in South Africa and Zimbabwe. The main gap identified in empirical literature is the omission of Social media use in technology adoption models and Social Networking theories. While some theories acknowledge the role of Social influences in technology adoption, the Social interactions considered therein are not mediated through the internet as is Social media. Furthermore, no empirical study has to date focused on how Social media influences mobile money technology adoption. Thus, this study deviates from the Offline Social Network analysis approach which is restricted to the neighbourhood effects, physical contact, cell phone calls and text messages where information on mobile money technology is disseminated to an individual’s limited Social circle. The secondary data used for the study were obtained from individual responses in the cross-sectional FinScope consumer surveys South Africa 2015 and Zimbabwe 2014 which were conducted and reported by FinMark Trust (2015; 2014). The study employed the binary logistic regression model to estimate the nature of effect. The results of the study indicated that use of Social media had a positive and statistically significant impact on mobile money adoption in both South Africa and Zimbabwe. The results also revealed that despite there being a lower internet penetration and Social media usage rate in Zimbabwe than South Africa, the use of Social media in the former led to a higher rate of mobile money adoption. The study also established that mere use of Social media and availability of mobile money technology did not translate to a high adoption rate; instead, availability had to be matched by a demand for the financial services. Additionally, the study found that the interaction of mobile money adoption and use of Social media increased the overall mobile money adoption in both countries. The study recommended the implementation of collective policies that increase internet penetration to facilitate increased use of Social media platforms and promote mobile money adoption to foster improved financial inclusion in developing countries.Hierdie studie het die gevolge van sosiale media op die ingebruikneming van mobiele geld in Suid-Afrika en Zimbabwe ondersoek. Die belangrikste leemte wat in empiriese literatuur geïdentifiseer is, is die weglating van die gebruik van sosiale media in tegnologieaanvaardingsmodelle en sosialenetwerkvorming-teorieë. Hoewel sommige teorieë (teorie van beredeneerde handeling; teorie van beplande gedrag; diffusie van innovasie) die rol van sosiale invloede op tegnologieaanvaarding erken, word die sosiale interaksies wat daarin oorweeg word nie deur middel van die internet bemiddel nie, soos wel in die geval van sosiale media. Boonop het geen empiriese studie tot op hede gefokus op hoe sosiale media die ingebruikneming van mobielegeld-tegnologie beïnvloed nie. Hierdie studie wyk dus af van die niegekoppelde sosialenetwerkontleding-benadering, wat beperk is tot die omgewingsgevolge, fisieke kontak, selfoonoproepe en teksboodskappe, waar inligting oor mobielegeld-tegnologie aan ʼn individu se beperkte sosiale kring versprei word. Die sekondêre data wat vir die studie gebruik is, is verkry uit afsonderlike response in die deursnee- FinScope-verbruikersopnames (Suid-Afrika 2015 en Zimbabwe 2014), wat onderneem en bekendgemaak is deur FinMark Trust (2015; 2014). Die studie maak gebruik van die binêre logistiese regressiemodel om die aard van effek te skat. Studiebevindings dui daarop dat die gebruik van sosiale media ’n positiewe en statisties beduidende uitwerking op die ingebruikneming van mobiele geld in sowel Suid-Afrika as Zimbabwe het. Die resultate wys ook dat, ondanks ’n laer internetpenetrasie en sosialemedia-gebruikskoers in Zimbabwe, die gebruik van sosiale media in Zimbabwe tot ’n hoër koers van ingebruikneming van mobiele geld in dié land as in Suid-Afrika tot gevolg het. Daar word verder waargeneem dat die blote gebruik van sosiale media en die beskikbaarheid van mobielegeld-tegnologie nie geredelik omgesit kan word in ’n hoë ingebruiknemingskoers nie; beskikbaarheid moet met ’n vraag na die finansiële dienste gepaard gaan. Daarbenewens toon die studie dat die interaksie tussen mobielegeld-ingebruikneming en die gebruik van sosiale media die oorkoepelende ingebruikneming van mobiele geld in albei lande versterk. Die studie beveel die implementering van beleide aan wat internetpenetrasie verhoog om wydverspreide gebruik van sosiale media te fasiliteer, wat op sy beurt die ingebruikneming van mobiele geld sal bevorder, wat finansiële insluiting sal bevorder.Ucwaningo luphenyisise imiphumela ye-Social media ekwamukelweni kwe-mobile money eNingizimu Afrika naseZimbabwe. Igebe elikhulu eliphawuliwe kwimibhalo yobufakazi ukweqiwa kokussetshenziswa kwe-Social media ekwamukelweni kwama-technology adoption models kanye namathiyori e-Social Networking. Kodwa amanye amathiyori (i-theory of reasoned action; i-theory of planned behaviour; i-diffusion of innovation) amukela indima yemithelela ye-Social influences ekwamukelweni kwetheknoloji, ngokusebenzisana kwama-Social interactions abonelelwe lapha, awaxhunyaniswa nge-inthanethi, njenge-Social media. Kanti-ke futhi okunye, akukho bufakazi bocwaningo kuze kubemanje obugxile kwindlela i-Social media enomthelela ngayo kwi-mobile money technology adoption. Ngakho-ke, lolu cwaningo luyehluka kwizinqubo ze-Offline Social Network analysis approach, enezihibe kwimiphumela esondelene nayo, ukuxhumana ngokubamba, ukushayelana izingcingo nge-cellphone, kanye nemilayezo ebhaliwe, lapho ulwazi kwi-mobile money technology lusatshalaliswa kumuntu ngamunye nalabo asondelene nabo. I-secondary data esetshenzisiwe kucwaningo itholakale kwizimpendulo zabantu ngamunye kwi-cross-sectional FinScope consumer surveys (iNingizimu Afrika 2015 kanye neZimbabwe 2014), olwenziwa nokubikwa nge-FinMark Trust (2015:2014). Ucwaningo lusebenzisa i-binary logistic regression model ukulinganisa inhlobo yomphumela. Imiphumela yocwaningo ikhombisa ukuthi i-Social media inomphumela omuhle futhi ngomphumela wezibalo ezibalulekile ekwamukelweni kwe-mobile money okwamukelwe kuwo womabili amazwe iNingizimu Afrika kanye neZimbabwe. Imiphumela ikhombise nokuthi, ngisho noma i-inthanethi ingakangeneleli kangako kwezinye izindawo, kodwa izinga lokusetshenziswa kwe-Social media eZimbabwe kungaphezulu kuneNingizimu Afrika, ukusetshenziswa eZimbabwe kuhola phambili ngezinga eliphezulu ekwamukelweni kwe-mobile money kunaseNingizimu Afrika. Kanti futhi kuphawulwa ukuthi ukusetshenziswa kwe-Social media kanye nokutholakala kwe-mobile money technology, akuhambelani ngezinga lokwamukelwa kakhulu; ukutholakala kumele kuhambelane nesidingeko samasevisi ezezimali. Nangaphezu kwalokho, ucwaningo lukhombisa ukuthi ukusebenzisana kokwamukelwa kwe-mobile money nokusetshenziswa kwe-Social media kuphakamisa ukwamukelwa kakhulu kwe-mobile money kuwo womabili amazwe. Ucwaningo luncoma ukuthi ukwamukelwa kwemigomo enyusa ukungenelela kakhulu kwe-inthanethi ukulekelela ukusetshenziswa kakhulu kwe-Social media, kanti futhi lokhu okuzophakamisa kakhulu ukwamukelwa kwe-mobile money okusiza ukubandakanya wonke kwezezimali.Business ManagementD. Phil. (Management Studies
Thomas V Pollet - One of the best experts on this subject based on the ideXlab platform.
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use of Social Network sites and instant messaging does not lead to increased Offline Social Network size or to emotionally closer relationships with Offline Network members
Cyberpsychology Behavior and Social Networking, 2011Co-Authors: Thomas V Pollet, Sam G B Roberts, R I M DunbarAbstract:The effect of Internet use on Social relationships is still a matter of intense debate. This study examined the relationships between use of Social media (instant messaging and Social Network sites), Network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using Social media was associated with a larger number of online Social Network "friends." However, time spent using Social media was not associated with larger Offline Networks, or feeling emotionally closer to Offline Network members. Further, those that used Social media, as compared to non-users of Social media, did not have larger Offline Networks, and were not emotionally closer to Offline Network members. These results highlight the importance of considering potential time and cognitive constraints on Offline Social Networks when examining the impact of Social media use on Social relationships.
Sam G B Roberts - One of the best experts on this subject based on the ideXlab platform.
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use of Social Network sites and instant messaging does not lead to increased Offline Social Network size or to emotionally closer relationships with Offline Network members
Cyberpsychology Behavior and Social Networking, 2011Co-Authors: Thomas V Pollet, Sam G B Roberts, R I M DunbarAbstract:The effect of Internet use on Social relationships is still a matter of intense debate. This study examined the relationships between use of Social media (instant messaging and Social Network sites), Network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using Social media was associated with a larger number of online Social Network "friends." However, time spent using Social media was not associated with larger Offline Networks, or feeling emotionally closer to Offline Network members. Further, those that used Social media, as compared to non-users of Social media, did not have larger Offline Networks, and were not emotionally closer to Offline Network members. These results highlight the importance of considering potential time and cognitive constraints on Offline Social Networks when examining the impact of Social media use on Social relationships.
Mingsyan Chen - One of the best experts on this subject based on the ideXlab platform.
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qmsampler joint sampling of multiple Networks with quality guarantee
arXiv: Social and Information Networks, 2015Co-Authors: Honghan Shuai, Denian Yang, Chihya Shen, Mingsyan ChenAbstract:Because Online Social Networks (OSNs) have become increasingly important in the last decade, they have motivated a great deal of research on Social Network analysis (SNA). Currently, SNA algorithms are evaluated on real datasets obtained from large-scale OSNs, which are usually sampled by Breadth-First-Search (BFS), Random Walk (RW), or some variations of the latter. However, none of the released datasets provides any statistical guarantees on the difference between the crawled datasets and the ground truth. Moreover, all existing sampling algorithms only focus on crawling a single OSN, but each OSN is actually a sampling of a global Offline Social Network. Hence, even if the whole dataset from a single OSN is crawled, the results may still be skewed and may not fully reflect the properties of the global Offline Social Network. To address the above issues, we have made the first attempt to explore the joint sampling of multiple OSNs and propose an approach called Quality-guaranteed Multi-Network Sampler (QMSampler) that can crawl and jointly sample multiple OSNs. QMSampler provides a statistical guarantee on the difference between the crawled real dataset and the ground truth (the perfect integration of all OSNs). Our experimental results demonstrate that the proposed approach generates a much smaller bias than any existing method. QMSampler has also been released as a free download.
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on multi Network sampling with quality guarantee
arXiv: Data Structures and Algorithms, 2013Co-Authors: Honghan Shuai, Denian Yang, Chihya Shen, Mingsyan ChenAbstract:Online Social Networks (OSNs) have been gaining increasing importance in the past decade and inspired many researches for Social Network analysis (SNA). Currently, SNA algorithms are evaluated with real datasets obtained from large-scale real OSNs, which are usually sampled by Breadth-First-Search (BFS), Random Walk (RW), and some variations. However, BFS and RW have been proven to introduce bias, and thus it is more difficult for the analysis results on those datasets to provide useful insights for the OSNs. Most importantly, none of the released datasets have provided any statistical guarantees on the difference of the crawled datasets and the ground truth. On the other hand, all existing sampling algorithms only focus on crawling a single OSN, but each OSN is actually a sampling from the global Offline Social Network. In other words, even if one crawls the whole dataset from a single OSN, the results may still be skewed and unable to fully reflect the properties of the global Offline Social Network. In this paper, therefore, we make the first attempt and propose Quality-guaranteed Multi-Network Sampler (QMSampler) to crawl and sample multiple OSNs jointly. QMSampler provides a statistical guarantee on the difference of the crawled real dataset and the ground truth (the perfect integration of all OSNs). Experimental results manifest that QMSampler generates much smaller bias than the existing approaches, and QMSampler is released as a free download.
