Relevant bibliographies by topics / Social influence

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Social influence'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 October 2024

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Journal articles on the topic "Social influence"

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Smith, Brian G., Megan C. Kendall, Devin Knighton, and Temi Wright. "Rise of the Brand Ambassador: Social Stake, Corporate Social Responsibility and Influence among the Social Media Influencers." Communication Management Review 03, no. 01 (July 30, 2018): 6–29. http://dx.doi.org/10.22522/cmr20180127.

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Ju, Weijia, and Ling Chen. "Influence Maximization in Social Network with Negative Influence." International Journal of Machine Learning and Computing 9, no. 2 (April 2019): 230–35. http://dx.doi.org/10.18178/ijmlc.2019.9.2.791.

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McDonald, Rachel I., and Christian S. Crandall. "Social norms and social influence." Current Opinion in Behavioral Sciences 3 (June 2015): 147–51. http://dx.doi.org/10.1016/j.cobeha.2015.04.006.

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Assensoh-Kodua, Akwesi. "Social purchasing and the influence of social networking: a conceptual view." Banks and Bank Systems 11, no. 3 (October 12, 2016): 44–57. http://dx.doi.org/10.21511/bbs.11(3).2016.05.

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Internet has enabled businesses to offer their merchandise through web-based applications, of which recent phenomenon includes online social networks (OSNs). This paper studies the influence of OSNs through the lens of perceived trust (PT), social norm (SN), user satisfaction (US) and perceived behavioral control (PBC) to find out how these influence participants of OSNs continuance buying intention. A model of IS continuance intention of web-based application was developed to test the above factors. The results show that trust in OSN is based mainly on the degree of the social relations that users have with their vendors, because they are members on the network, on top of their experiences of web service use. US was influenced by PBC, while US also influenced SN and PT with PT exhibiting a strong relationship with SN. Keywords: continuance intention, OSN, participants, purchasing. JEL Classification: Z13, G21, M10, M31, D11, D12
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Dr R Venkatapathy, Dr R. Venkatapathy, and Valarrmathi V. Valarrmathi V. "Innovative Trends in Corporate Social Responsibility and Influence of Social Media." Global Journal For Research Analysis 3, no. 4 (June 15, 2012): 234–35. http://dx.doi.org/10.15373/22778160/apr2014/81.

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Okdie, Bradley M., Rosanna E. Guadagno, Petia K. Petrova, and Wyley B. Shreves. "Social Influence Online." International Journal of Interactive Communication Systems and Technologies 3, no. 1 (January 2013): 20–31. http://dx.doi.org/10.4018/ijicst.2013010102.

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This study examined the extent to which communicator salience manipulated by varying communication modes, authority-based social influence, and gender affect persuasion in online environments by utilizing a 2 by 2 between subjects design. Participants of the experiment were either presented with an authority-based influence attempt or no influence attempt. They then engaged in a persuasive interaction with a same-sex confederate via computer-mediated communication (CMC) or face-to-face. Results revealed that men in the Authority condition who interacted via CMC were more persuaded then men in the Peer condition who interacted via CMC. Additionally, men reported more confidence when interacting via CMC and reported that their decision was more influenced by the confederate online. Moreover, perceptions of the confederate varied by gender and communication mode. Analysis suggests that authority based influence tactics via CMC are more effective for men than for women.
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Dallas, Rebecca, Matt Field, Andrew Jones, Paul Christiansen, Abi Rose, and Eric Robinson. "Influenced but Unaware: Social Influence on Alcohol Drinking Among Social Acquaintances." Alcoholism: Clinical and Experimental Research 38, no. 5 (March 3, 2014): 1448–53. http://dx.doi.org/10.1111/acer.12375.

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Gomes, Adriano José da Silva, Juliana Francisca Cecato, José Montiel, José Eduardo Martinelli, and Gleiber Couto Santos. "Influence of Social Skills in educational processes." Perspectivas Médicas 25, no. 1 (April 1, 2014): 20–26. http://dx.doi.org/10.6006/perspectmed.20140103.5720327683.

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ANDRONIC, Răzvan-Lucian, and Anca-Olga ANDRONIC. "EVALUATION AND SOCIAL INFLUENCE IN SCHOOL EDUCATION." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 2 (June 24, 2016): 505–8. http://dx.doi.org/10.19062/2247-3173.2016.18.2.2.

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Offermann, Lynn R., and Pamela E. Schrier. "Social Influence Strategies." Personality and Social Psychology Bulletin 11, no. 3 (September 1985): 286–300. http://dx.doi.org/10.1177/0146167285113005.

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Dissertations / Theses on the topic "Social influence"

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Mason, Winter. "Implicit social influence." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3278231.

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Thesis (Ph.D.)--Indiana University, Dept. of Psychological and Brain Sciences, 2007.
Source: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 6391. Adviser: Eliot R. Smith. Title from dissertation home page (viewed May 9, 2008).
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Hopkins, N. "Adolescent social groups and social influence." Thesis, University of Exeter, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384707.

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Gamal, Doaa. "Social Networks Influence Analysis." UNF Digital Commons, 2017. http://digitalcommons.unf.edu/etd/723.

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Pew Research Center estimates that as of 2014, 74% of the Internet Users used social media, i.e., more than 2.4 billion users. With the growing popularity of social media where Internet users exchange their opinions on many things including their daily life encounters, it is not surprising that many organizations are interested in learning what users say about their products and services. To be able to play a proactive role in steering what user’s say, many organizations have engaged in efforts aiming at identifying efficient ways of marketing certain products and services, and making sure user reviews are somewhat favorable. Favorable reviews are typically achieved through identifying users on social networks who have a strong influence power over a large number of other users, i.e. influential users. Twitter has emerged as one of the prominent social network services with 320 million monthly active users worldwide. Based on the literature, influential Twitter users have been typically analyzed using the following three models: topic-based model, topology-based model, and user characteristics-based model. The topology-based model is criticized for being static, i.e., it does not adapt to the social network changes such as user’s new posts, or new relationships. The user characteristics-based model was presented as an alternative approach; however, it was criticized for discounting the impact of interactions between users, and users’ interests. Lastly, the topic-based model, while sensitive to users’ interests, typically suffers from ignoring the inclusion of inter-user interactions. This thesis research introduces a dynamic, comprehensive and topic-sensitive approach for identifying social network influencers leveraging the strengths of the aforementioned models. Three separate experiments were conducted to evaluate the new approach using the information diffusion measure. In these experiments, software was developed to capture users’ tweets pertinent to a topic over a period of time, and store the tweet’s metadata in a relational database. A graph representing users was extracted from the database. The new approach was applied to the users’ graph to compute an influence score for each user. Results show that the new composite influence score is more accurate in comprehensively identifying true influential users, when compared to scores calculated using the characteristics-based, topic-based, and topology-based models. Also, this research shows that the new approach could leverage a variety of machine learning algorithms to accurately identify influencers. Last, while the focus of this research was on Twitter, our approach may be applicable to other social networks and micro-blogging services.
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Bolletta, Ugo <1986&gt. "Social Influence in Networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amsdottorato.unibo.it/7332/1/Bolletta_Ugo_Tesi.pdf.

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This thesis is composed by three standalone papers. The first chapter is about opinion formation processes. Individuals influence each other according to the network structure. If the network is connected and satisfies other mild assumptions, the society will reach a consensus. Therefore, it is a matter of interest understanding when the network would be connected or not. Here, we develop a model where the network takes place endogenously, and agents update their opinions accordingly. We study general conditions on the initial distribution of opinions such that consensus will be reached. We provide sufficient conditions for connectedness. In the dynamic model we show that polarization both in the transition and the long run. This essay is a joint work with Paolo Pin (Bocconi University). The second chapter is about peer effects. I consider how social pressure affects the strategic network formation process. Agents choose their links subject to mutual consent, and then equilibrium behaviors are determined by an underlying game where agents choose their effort. I provide a characterization result for all pairwise Nash stable network, and use farsightedness to avoid cycles. As an application, I consider peer effects in the classroom. Results suggest that we could set optimal policies to improve outcome of low achievement students through targeted incentives schemes. In the last chapter I focus on the interaction between real and virtual life. To do so I propose a model of search where agents choose in equilibrium how intense is their on-line activity. The outcomes of the game depend on the network, which takes place through a semi-random process. I extend the standard random network formation allowing agents to hold a certain degree of choice. The model allows to track characteristics on the meeting environment and individual preferences that would make virtual and real life substitutes or complements.
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Martin, R. P. A. "Minority influence and social categorization." Thesis, Open University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380798.

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Tolunay, Adviye. "Group identity effects on social influence /." View online ; access limited to URI, 2005. http://0-wwwlib.umi.com.helin.uri.edu/dissertations/dlnow/3186924.

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Vedanarayanan, Srinivasa Raghavan. "Agents of Influence in Social Networks." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342464356.

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Dudte, Kari A. "Social influence and gender norms." Connect to resource, 2008. http://hdl.handle.net/1811/32098.

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Sigala, Maria. "Tax compliance and social influence." Thesis, University of Exeter, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302572.

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Andersson, Maria. "Social influence in stock markets." Gothenburg : Department of Psychology, University of Gothenburg, 2009. http://gupea.ub.gu.se/dspace/handle/2077/20506.

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Books on the topic "Social influence"

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Turner, John C. Social influence. Milton Keynes: OpenUNiversity Press, 1991.

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P, Zanna Mark, Olson James M. 1953-, and Herman C. Peter 1946-, eds. Social influence. Hillsdale, N.J: L. Erlbaum Associates, 1987.

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Xu, Wen, and Weili Wu. Optimal Social Influence. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37775-5.

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Trenholm, Sarah. Persuasion and social influence. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Inc, NetLibrary, ed. Social influences. London: Routledge, 1999.

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Goldsmith, Elizabeth B. Social Influence and Sustainable Consumption. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20738-4.

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Edwards, John, R. Scott Tindale, Linda Heath, and Emil J. Posavac, eds. Social Influence Processes and Prevention. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4899-2094-2.

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Wärneryd, Karl-Erik. Social influence on economic behaviour. Brussels: European Institute ForAdvanced Studies in Management, 1987.

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John, Edwards, Loyola University of Chicago. Applied Social Psychology Graduate Program., and Society for the Psychological Study of Social Issues., eds. Social influence processes and prevention. New York: Plenum Press, 1990.

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R, Berger Charles, and Burgoon Michael, eds. Communication and social influence processes. East Lansing: Michigan State University Press, 1995.

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Book chapters on the topic "Social influence"

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Burger, Jerry M. "Social Influence." In Desire for Control, 63–79. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-9984-2_4.

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Sutton, Robbie, and Karen Douglas. "Social influence." In Social Psychology, 388–429. London: Macmillan Education UK, 2013. http://dx.doi.org/10.1007/978-1-137-29968-0_9.

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Eftekhar, Milad. "Social Influence." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80694-1.

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Davies, Roger, and Peter Houghton. "Social influence." In Mastering Psychology, 32–50. London: Macmillan Education UK, 1995. http://dx.doi.org/10.1007/978-1-349-13553-0_3.

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Malim, Tony, and Ann Birch. "Social influence." In Introductory Psychology, 677–701. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14186-9_34.

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Malim, Tony. "Social influence." In Social Psychology, 201–40. London: Macmillan Education UK, 1997. http://dx.doi.org/10.1007/978-1-349-14221-7_6.

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Evans, David C. "Social Influence." In Bottlenecks, 213–24. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2580-6_21.

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Collette, Tyler, and Richard L. Miller. "Social Influence." In Cross-Cultural Psychology, 549–74. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119519348.ch27.

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Gough, Brendan, Majella McFadden, and Matthew McDonald. "Social Influence." In Critical Social Psychology, 99–125. London: Macmillan Education UK, 2013. http://dx.doi.org/10.1007/978-1-137-07242-9_4.

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Hayes, Nicky. "Social influence." In Fundamentals of Social Psychology, 186–230. New York : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315157863-7.

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Conference papers on the topic "Social influence"

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de Maertelaere, Maikel, Ting Li, and Guido Berens. "Social influence." In the 14th Annual International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2346536.2346595.

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Bakshy, Eytan, Dean Eckles, Rong Yan, and Itamar Rosenn. "Social influence in social advertising." In the 13th ACM Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2229012.2229027.

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Wang, Ting, Mudhakar Srivatsa, Dakshi Agrawal, and Ling Liu. "Microscopic Social Influence." In Proceedings of the 2012 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611972825.12.

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Song, Changhao, Bo Wang, Qinxue Jiang, Yehua Zhang, Ruifang He, and Yuexian Hou. "Social Recommendation with Implicit Social Influence." In SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3404835.3463043.

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Oktavia, Tanty, Irsyad Nuryatama, Stephan Ardy, Andres Cello, Fernaldy Owen, and Nelson Susanto. "Social Media Influence on Social Justice." In 2023 International Conference on Information Management and Technology (ICIMTech). IEEE, 2023. http://dx.doi.org/10.1109/icimtech59029.2023.10278018.

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Tahbaz-Salehi, Alireza, Alvaro Sandroni, and Ali Jadbabaie. "Learning under social influence." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5399751.

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Tang, Fangshuang, Qi Liu, Hengshu Zhu, Enhong Chen, and Feida Zhu. "Diversified social influence maximization." In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921625.

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Guo, Yuning, Jianxiang Cao, and Weiguo Lin. "Social Network Influence Analysis." In 2019 6th International Conference on Dependable Systems and Their Applications (DSA). IEEE, 2020. http://dx.doi.org/10.1109/dsa.2019.00093.

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Churchill, Elizabeth. "Session details: Social influence." In CHI07: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2007. http://dx.doi.org/10.1145/3258909.

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"Session details: Social influence." In the SIGCHI Conference, chair Elizabeth Churchill. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1240624.3258909.

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Reports on the topic "Social influence"

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Cho, Eunjoo, Jihyeong Son, and Ann Marie Fiore. Influence of Social Connectedness on Apparel Purchases through Social Commerce. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-358.

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Boff, Kenneth R. Social Cultural Dynamics of Trust, Influence and Persuasion. Fort Belvoir, VA: Defense Technical Information Center, August 2015. http://dx.doi.org/10.21236/ada623519.

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Miller, Clara. Indications of feminist influence on contemporary social work practice. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2769.

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Advani, Arun. Social connectedness: and its influence on participation in risky behaviour. The IFS, August 2011. http://dx.doi.org/10.1920/ps.ifs.2024.0971.

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Rando Cueto, D., JF Paniagua Rojano, and C. de las Heras Pedrosa. Influence factors on the success of hospital communication via social networks. Revista Latina de Comunicación Social, November 2016. http://dx.doi.org/10.4185/rlcs-2016-1140en.

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Bernardi, Laura. Determinants of individual AIDS risk perception: knowledge, behavioural control, and social influence. Rostock: Max Planck Institute for Demographic Research, July 2002. http://dx.doi.org/10.4054/mpidr-wp-2002-029.

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Bernardi, Laura, Holger von der Lippe, and Sylvia Keim. Mapping social influence on fertility: a mix-method approach to data collection. Rostock: Max Planck Institute for Demographic Research, June 2005. http://dx.doi.org/10.4054/mpidr-wp-2005-015.

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Carlisle, Tracy. Influence of Articulation and Phonology Intervention on Children's Social and Emotional Characteristics. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7119.

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Johnson, Jennifer, and Young Ha. Modern consumer socialization: The influence of peers, family, and online social networking usage. Ames: Iowa State University, Digital Repository, 2013. http://dx.doi.org/10.31274/itaa_proceedings-180814-496.

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Atran, Scott, Douglas Medin, Richard Davis, Jeremy Ginges, Robert Axelrod, and Juan Zarate. Mutual Influence of Moral Values, Mental Models and Social Dynamics on Intergroup Conflict. Fort Belvoir, VA: Defense Technical Information Center, April 2010. http://dx.doi.org/10.21236/ada523370.

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