Advertisement

The Intersection of Source, Message, and Recipient Characteristics on Information-Exchange Activity via Twitter

  • Mohammad AlajmiEmail author
  • Huda Farhan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9844)

Abstract

The purpose of the research is to explain how Twitter supports real-time information exchange in popular domains, and examine the influence of source, message, and recipient characteristics on information exchange. University students were surveyed using a structured questionnaire. A model was developed and statistically tested to examine the influence of characteristics on information exchange via Twitter. Different characteristics were demonstrated to be significant predictors of information exchange. For source characteristics, authoritative knowledge, social connections, and attractiveness have a positive influence, while for recipient characteristics, prior knowledge, community engagement, and demographics influence information exchange. For message characteristics, information usefulness and information quality are effective. Overall, influences vary based on the domain. The results help Twitter operators and users to understand the most important source, message, and recipient characteristics for information exchange. This study informs sources about the characteristics that make tweets more informative, and more likely to be exchanged by recipients. It assists Twitter operators to understand what characteristics are important in future system designs.

Keywords

Source characteristics Message characteristics Recipient characteristics Microblogging Information seeking Information sharing Information exchange 

Notes

Acknowledgments

This work supported and funded by The Public Authority of Education and Training, Research project No. (BF-15-12), Research Title (The Intersection of Source, Message, and Recipient Characteristics on Information-Exchange Activity via Twitter).

References

  1. 1.
    Ribière, V., Haddad, M., Wiele, P.: The impact of national culture traits on the usage of web 2.0 technologies. J. Inf. Knowl. Manag. Syst. 40(3/4), 334–361 (2010)Google Scholar
  2. 2.
    Shen, X., Zhang, K., Zhao, S.: Understanding information adoption in online review communities: the role of herd factors. In: 47th Hawaii International Conference on System Science, 6–9 January, Waikoloa, Hawaii, USA (2014)Google Scholar
  3. 3.
    Java, A., Song, X., Finin, T., Tseng, B.: Why we Twitter: understanding microblogging usage and communities. In: 9th WEBKDD and 1st SNA-KDD Workshop, 12–15 August, San Jose, CA, USA (2007)Google Scholar
  4. 4.
    Peterson, R.D.: To tweet or not to tweet: exploring the determinants of early adoption of Twitter by house members in the 111th congress. Soc. Sci. J. 49(4), 430–438 (2012)CrossRefGoogle Scholar
  5. 5.
    Wilson, T.: Models in information behavior research. J. Doc. 55(3), 249–270 (1999)CrossRefGoogle Scholar
  6. 6.
    Johan, Y., Mao, H., Zeng, X.: Twitter mood predicting the stock market. J. Comput. Sci. 3(1), 1–8 (2011)Google Scholar
  7. 7.
    Witkemper, C., Lim, C., Waldburger, A.: Social media and sports marketing: examining the motivations and constraints of Twitter users. Sport Mark. Q. 21, 170–183 (2012)Google Scholar
  8. 8.
    Sreenivasan, N., Lee, C., Goh, D.: Tweeting the friendly skies: investigating information exchange among Twitter users about airlines. Electron. Libr. Inf. Syst. 46(1), 21–42 (2012)Google Scholar
  9. 9.
    Scanfeld, D., Scanfeld, V., Larson, E.: Dissemination of health information through social networks: Twitter and antibiotic. Am. J. Infect. Control 38(3), 182–188 (2010)CrossRefGoogle Scholar
  10. 10.
    Chung, D., Kim, S.: Blogging activity among cancer patients and their companions: uses, gratifications, and predictors of outcomes. J. Am. Soc. Inform. Sci. Technol. 59(2), 297–306 (2008)CrossRefGoogle Scholar
  11. 11.
    Cheung, M., Lou, C., Sia, C., Chen, H.: Credibility of electronic word-of-mouth: information and normative determinants of on-line consumer recommendation. Int. J. Electron. Commer. 13(4), 9–38 (2009)CrossRefGoogle Scholar
  12. 12.
    Liu, Z., Liu, L., Li, H.: Determinants of information retweeting in microblogging. Internet Res. 22(4), 443–466 (2012)CrossRefGoogle Scholar
  13. 13.
  14. 14.
    Hersberger, J., Murray, A., Rioux, K.: Examining information exchange and virtual communities: an emergent framework. Online Inf. Rev. 31(2), 135–147 (2007)CrossRefGoogle Scholar
  15. 15.
    Virkus, S.: Use of Web 2.0 technologies in LIS education: experiences at Tallinn university, Estonia. Program: Electron. Libr. Inf. Syst. 42(3), 262–274 (2008)CrossRefGoogle Scholar
  16. 16.
    Matschke, C., Moskaliuk, J., Bokhorst, F., Schummer, T., Cress, U.: Motivational factors of information exchange in social information spaces. Comput. Hum. Behav. 36, 549–558 (2014)CrossRefGoogle Scholar
  17. 17.
    Belkin, N.: Information concepts for information science. J. Doc. 34(1), 55–85 (1978)CrossRefGoogle Scholar
  18. 18.
    Buckland, M.: Information as thing. J. Am. Soc. Inf. Sci. 42(5), 351–360 (1991)CrossRefGoogle Scholar
  19. 19.
    Dervin, B.: Useful theory for librarianship: communication not information. Drexel Libr. Q. 13(3), 16–32 (1977)Google Scholar
  20. 20.
    Kim, S.: Factors affecting the use of social software: TAM perspectives. Electron. Libr. 30(50), 690–706 (2012)CrossRefGoogle Scholar
  21. 21.
    Smock, A., Ellison, N., Lampe, C., Wohn, D.: Facebook as a toolkit: a uses and gratifications approach to unbundling feature use. Comput. Hum. Behav. 27(6), 2322–2329 (2011)CrossRefGoogle Scholar
  22. 22.
    Holton, A., Baek, K., Coddington, M., Yaschur, C.: Seeking and sharing: motivations for linking on Twitter. Commun. Res. Rep. 31(1), 33–40 (2014)CrossRefGoogle Scholar
  23. 23.
    Earp, J., Ott, M., Pozzi, F.: Facilitating educators’ knowledge sharing with dedicated information systems. Comput. Hum. Behav. 29(2), 445–455 (2013)CrossRefGoogle Scholar
  24. 24.
    Mir, I., Rehman, K.: Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Manag. Mark. Chall. Knowl. Soc. 8(4), 637–654 (2013)Google Scholar
  25. 25.
    Jansen, B., Zhang, M., Sobel, K., Chowdury, A.: Twitter power: tweets as electronic word of mouth. J. Am. Soc. Inf. Sci. Technol. 69(9), 1–20 (2009)Google Scholar
  26. 26.
    Zhang, J., Qu, Y., Cody, J., Wu, Y.: A case study of microblogging in the enterprise: use, value, and related issues. In: Proceedings of the 28th International Conference of Human Factors in Computing Systems CHI 2010 (2011)Google Scholar
  27. 27.
    Romero, D., Meeder, B., Kleinberg, J.: Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on Twitter. In: Proceedings of the 20th International Conference on the World Wide Web in New York, 28 March–1 April 2011, Hyderabad, India, pp. 695–704 (2011)Google Scholar
  28. 28.
    Remy, C., Pervin, N., Toriumi, F., Takeda, H.: Information diffusion on Twitter: everyone has its chance, but all chances are not equal. In: International Conference on Signal-Image Technology and Internet-Based Systems, 2–5 December, Kyoto, pp. 483–490 (2013)Google Scholar
  29. 29.
    Suh, B., Hong, L., Pirolli, P., Chi, E.: Want to be retweeted? Large scale analytics on factors impacting retweet in Twitter network. In: IEEE International Conference on Social Computing, pp. 177–184 (2010)Google Scholar
  30. 30.
    Bakshy, E., Hofman, J., Mason, W., Watts, D.: Everyone’s an influencer: quantifying influence on Twitter. In: WSDM 2011, Proceedings of the Fourth ACM International Conference on Web Search and Data Mining in Hong Kong, 9–12 February, pp. 64–74. ACM, New York (2011)Google Scholar
  31. 31.
    Cress, U.: Mass collaboration – an emerging field for CSCL research. In: Rummel, N., Kapur, M., Nathan, N., Puntambekar, S. (Eds.) To see the World and a Grain of Sand: Learning Across Levels of Space and Scale: CSCL 2013 Proceedings, vol. 1, pp. 557–563. International Society of the Learning Sciences Madison, USA (2013)Google Scholar
  32. 32.
    Hovland, C., Janis, I., Kelley, H.: Communication Change and Persuasion: Psychological Studies of Opinion Change. Yale University Press, New Haven (1953)Google Scholar
  33. 33.
    Deutsch, M., Gerard, H.: A study of normative and informational social influence upon individual judgments. J. Abnorm. Soc. Psychol. 53(3), 629–636 (1955)CrossRefGoogle Scholar
  34. 34.
    Petty, R., Cacioppo, J.: Communication and Persuasion: Central and Peripheral Routes to Attitude Change. Springer, New York (1986)CrossRefGoogle Scholar
  35. 35.
    Chaiken, S.: Heuristic versus systematic information processing and the use of source versus message cues in persuasion. J. Pers. Soc. Psychol. 39(5), 752–766 (1980)CrossRefGoogle Scholar
  36. 36.
    Doyle, J., Heslop, L., Ramirez, A., Cray, D.: Trust intentions in readers of blogs. Manag. Res. Rev. 35(9), 837–856 (2012)CrossRefGoogle Scholar
  37. 37.
    Bongwon, S., Lichan, H., Peter, P., Chi, E.: Want to be retweeted? Large scale analytics on factors impacting retweet in Twitter network. In: Proceedings of the 2010 IEEE International Conference on Privacy, Security, Risks and Trust, pp. 177–184 (2010)Google Scholar
  38. 38.
    Burgoon, J., Bonito, J., Bengtsson, B., Cederberg, C., Lundeberg, M., Allspach, L.: Interactivity in human-computer interaction: a study of credibility, understanding and influence. Comput. Hum. Behav. 16(6), 553–574 (2000)CrossRefGoogle Scholar
  39. 39.
    Chen, W., Hirschheim, R.: A paradigmatic and methodological examination of information systems research from 1991 to 2001. Inf. Syst. J. 14(3), 197–235 (2004)CrossRefGoogle Scholar
  40. 40.
    Nahapiet, J., Ghoshal, S.: Social capital, intellectual capital and the organization advantage. Acad. Manag. Rev. 23(2), 242–266 (1998)Google Scholar
  41. 41.
    Tsai, W., Ghoshal, S.: Social capital and value creation: the role of intrafirm networks. Acad. Knowl. Manag. 41(4), 464–476 (1998)CrossRefGoogle Scholar
  42. 42.
    Steinfield, C., Ellison, N.B., Lampe, C.: Social capital, self-esteem, and use of online social network sites: a longitudinal analysis. J. Appl. Dev. Psychol. 29, 434–445 (2008)CrossRefGoogle Scholar
  43. 43.
    Lin, N.: Building a network theory of social capital. Connections 22(1), 28–51 (1999)Google Scholar
  44. 44.
    Dike, S., Singh, K.: Applications of social capital in educational literature: a critical synthesis. Rev. Educ. Res. 72(1), 31–69 (2002)CrossRefGoogle Scholar
  45. 45.
    Mayer, R., Davis, J., Schoorman, F.: An integrative model of organizational trust. Acad. Manag. Rev. 20(3), 709–734 (1995)Google Scholar
  46. 46.
    McKnight, D., Choudhury, V., Kacmar, C.: Developing and validating trust measures for e-commerce: an integrative typology. Inf. Syst. Res. 13(3), 334–359 (2002)CrossRefGoogle Scholar
  47. 47.
    Wathen, C.N., Burkell, J.: Believe it or not: factors influencing credibility on the web. J. Am. Soc. Inform. Sci. Technol. 53(2), 134–144 (2002)CrossRefGoogle Scholar
  48. 48.
    Sin, S.J., Kim, K.: International students’ everyday life information seeking: the information value of social networking sites. Libr. Inf. Sci. Res. 34(2), 107–116 (2013)CrossRefGoogle Scholar
  49. 49.
    Fulk, J., Schmitz, J., Steinfield, C.W.: A social influence model of technology use. In: Fulk, J., Steinfield, C. (eds.) Organizations and Communication Technology, pp. 117–140. Sage, Newbury Park (1990)CrossRefGoogle Scholar
  50. 50.
    Awad, N.F., Ragowsky, A.: Establishing trust in electronic commerce through online word of mouth: An examination across genders. J. Manag. Inf. Syst. 24(4), 101–121 (2008)CrossRefGoogle Scholar
  51. 51.
    Katungi, E., Edmeades, S., Smale, M.: Gender, social capital, and information exchange in rural Uganda. J. Int. Dev. 20(1), 35–52 (2008)CrossRefGoogle Scholar
  52. 52.
    Liu, C.: Gender differences in the determinants of sharing information via mobile phones. J. Int. Technol. Inf. Manag. 19(4), 61–75 (2010)Google Scholar
  53. 53.
    Pfeil, U., Arjan, R., Zaphiris, P.: Age differences in online social networking: a study of user profiles and the social capital divide among teenagers and older users in myspace. Comput. Hum. Behav. 25(3), 643–654 (2009)CrossRefGoogle Scholar
  54. 54.
    Valenzuela, S., Park, N., Kee, K.: Is there social capital in a social network site? Facebook use and college students’ life satisfaction, trust and participation. J. Comput.-Mediat. Commun. 14(4), 875–901 (2009)CrossRefGoogle Scholar
  55. 55.
    Salem, F., Mourtada, R., Al-Shaer, S.: Citizen engagement and public services in the Arab world: the potential of social media. Arab Social Media Report, pp. 1–54 (2014)Google Scholar
  56. 56.
    Mazman, S.G., Usluel, Y.K.: Gender differences in using social networks. Turkish Online J. Educ. Technol. 10(2), 133–139 (2011)Google Scholar
  57. 57.
    Lin, K., Lu, H.: Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput. Hum. Behav. 27(3), 1152–1161 (2011)CrossRefGoogle Scholar
  58. 58.
    Easterby-Smith, M., Golden-Biddle, K., Locke, K.: Working with pluralism: determining quality in qualitative research. Organ. Res. Methods 11(3), 419–429 (2008)CrossRefGoogle Scholar
  59. 59.
    Bosman, D., Boshoff, C., Rooyen, G.: The review credibility of electronic word-of-mouth communication on e-commerce platforms. Manag. Dyn. 22(3), 29–44 (2013)Google Scholar
  60. 60.
    Kabe, K.: Twenty five influenced tweets in the general political issue. Al Qabas, 22 January 2015Google Scholar
  61. 61.
    Head, A., Eisenberg, M.: How college students use the web to conduct everyday life research. First Monday 16(4) (2011)Google Scholar
  62. 62.
    Gall, M.D., Gall, J.P., Borg, W.R.: Educational Research: An Introduction. Pearson Education, Boston (2007)Google Scholar
  63. 63.
    Zhou, T., Li, H., Liu, Y.: The effect of flow experience on mobile SNS users’ loyalty. Ind. Manag. Data Syst. 110(6), 930–946 (2010)MathSciNetCrossRefGoogle Scholar
  64. 64.
    Sussman, S.W., Siegal, W.S.: Informational influence in organizations: an integrated approach to knowledge adoption. Inf. Syst. Res. 14(1), 47–65 (2003)CrossRefGoogle Scholar
  65. 65.
    Cheung, C., Thadani, D.: The impact of electronic word-of-mouth communication: a literature analysis and integrative model. Decis. Support Syst. 54(1), 461–470 (2012)CrossRefGoogle Scholar
  66. 66.
    Shin, D.: What do people do with digital multimedia broadcasting? Path analysis of structural equation modeling. J. Mob. Commun. 6(1), 258–275 (2008)CrossRefGoogle Scholar
  67. 67.
    Kim, K.H., Yun, H.: Crying for me, crying for us: relational dialectics in a Korean social network site. J. Comput.-Mediat. Commun. 13(1), 298–319 (2007)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  1. 1.Public Authority for Applied Education and TrainingKuwait CityKuwait

Personalised recommendations