Linganisha mbinu

	Social Media Network Analysis	Semantic Network Analysis
Nyanja	Communication	Communication
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2017	1999
Mwanzilishi	Social network analysis tradition (Wasserman & Faust); Himelboim et al. for platform typologies	George Barnett, Marya Doerfel, Steven Corman (communication applications)
Aina	Structural analysis of relationships among social-media actors	Network representation of concepts and their co-occurrence in text
Chanzo asilia	Himelboim, I., Smith, M. A., Rainie, L., Shneiderman, B., & Espina, C. (2017). Classifying Twitter topic-networks using social network analysis. Social Media + Society, 3(1), 1–13.	Corman, S. R., Kuhn, T., McPhee, R. D., & Dooley, K. J. (2002). Studying complex discursive systems: Centering resonance analysis of communication. Human Communication Research, 28(2), 157–206.
Majina mbadala	Social media SNA, Online interaction network analysis, Platform conversation network analysis, Sosyal Medya Ağ Analizi	Text network analysis, Concept co-occurrence network analysis, Centering resonance analysis, Anlamsal Ağ Analizi
Zinazohusiana	4	4
Muhtasari	Social media network analysis applies social-network methods to the relationships among accounts on platforms — who follows, mentions, replies to, retweets, or shares whom — to reveal the structure of online conversation. By representing interactions as a graph and computing measures of centrality and community, it identifies influential actors, cohesive clusters, and the overall shape of public discourse around a topic.	Semantic network analysis represents the meaning of a text or corpus as a network of concepts connected by their co-occurrence or grammatical proximity, then uses network-analytic measures to reveal which ideas are central, how concepts cluster, and how shared meaning is structured. In communication research it is the standard way to map the conceptual architecture of media coverage, organizational discourse, and public conversation at scale.