Measuring the Reach and Impact of Information Warfare
DOI:
https://doi.org/10.37266/ISER.2023v11i1-2.pp9-14Keywords:
Information WarfareAbstract
Information is a critical component of national power, with new information narratives emerging daily. While some narratives deserve attention by leaders, others lack enough traction to warrant attention. In the context of Information Warfare, leaders must understand key metrics of emerging narratives to determine their importance. Faced with the problem that leaders do not know if a social media story matters, we created a dashboard to aid leaders in identifying Information Warfare campaigns and their impacts. The methodology consisted of measuring four metrics of distinct narratives: reach, virality, propagation, and organic versus inorganic activity. Taken together, these metrics show how narratives spread, the speed of spread, authenticity, and impact. When packaged together in dashboard visualizations, these metrics enable informed decision making in strategic environments in the information dimension.
References
Balestrucci, A., & De Nicola, R. (2020). Credulous users and fake news: A real case study on the propagation in Twitter. In 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (p. 1-8).
Beskow, D. M., & Carley, K. M. (2018). Bot conversations are different: Leveraging network metrics for bot detection in twitter. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 825–832).
Beskow, D. M., & Carley, K. M. (2019). Social cybersecurity: An emerging national security requirement. Military Review, 99(2), 117-127.
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-mediated Communication, 13(1), 210–230.
Charmpi, K., Chokkalingam, M., Johnen, R., & Beyer, A. (2021). Optimizing network propagation for multi-omics data integration. PLoS Computational Biology, 17(11), e1009161.
Constantinides, E. (2014). Foundations of social media marketing. Procedia-Social and behavioral sciences, 148, 40–57.
Enginkaya, E., & Yılmaz, H. (2014). What drives consumers to interact with brands through social media? A motivation scale development study. Procedia-Social and Behavioral Sciences, 148, 219–226.
Hoang, T.-A., Lim, E.-P., Achananuparp, P., Jiang, J., & Zhu, F. (2011). On modeling virality of twitter content. In International conference on asian digital libraries (pp. 212–221).
Jiang, J., Wen, S., Yu, S., Xiang, Y., & Zhou, W. (2017). Identifying propagation sources in networks: State-of-the-art and comparative studies. IEEE Communications Surveys Tutorials, 19(1), 465-481.
Lee-Won, R. J., Abo, M. M., Na, K., & White, T. N. (2016). More than numbers: Effects of social media virality metrics on intention to help unknown others in the context of bone marrow donation. Cyberpsychology, Behavior, and Social Networking, 19(6), 404–411.
Li, L., Zhang, Q., Wang, X., Zhang, J., Wang, T., Gao, T.-L., … Wang, F.-Y. (2020). Characterizing the propagation of situational information in social media during covid-19 epidemic: A case study on weibo. IEEE Transactions on Computational Social Systems, 7(2), 556-562.
Murdough, C. (2009). Social media measurement: It’s not impossible. Journal of interactive advertising, 10(1), 94–99. Nelson-Field, K. (2013). Viral marketing: The science of sharing. Oxford University Press.
Tsugawa, S., & Ohsaki, H. (2017). On the relation between message sentiment and its virality on social media. Social Network Analysis and Mining, 7(1), 1–14.
Valenzuela, S. (2013). Unpacking the use of social media for protest behavior: The roles of information, opinion expression, and activism. American behavioral scientist, 57(7), 920–942.
Valenzuela, S., Arriagada, A., & Scherman, A. (2012). The social media basis of youth protest behavior: The case of Chile. Journal of Communication, 62(2), 299–314.
Published
How to Cite
Issue
Section
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
The copyediting stage is intended to improve the flow, clarity, grammar, wording, and formatting of the article. It represents the last chance for the author to make any substantial changes to the text because the next stage is restricted to typos and formatting corrections. The file to be copyedited is in Word or .rtf format and therefore can easily be edited as a word processing document. The set of instructions displayed here proposes two approaches to copyediting. One is based on Microsoft Word's Track Changes feature and requires that the copy editor, editor, and author have access to this program. A second system, which is software independent, has been borrowed, with permission, from the Harvard Educational Review. The journal editor is in a position to modify these instructions, so suggestions can be made to improve the process for this journal.