Lucia Falzon
Biographic Data
| ID | 636041 |
|---|---|
| NAME | Lucia Falzon |
| GIVEN NAMES | Lucia |
| FAMILY NAME | Falzon |
| SIGNATURE | FALZON L |
| AFFILIATIONS | Defence Science and Technology Group |
| ORCID | 0000-0003-3134-4351 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2000 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Exploring the effect of streamed social media data variations on social network analysis
Embedding time in positions: Temporal measures of centrality for social network analysis
Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra…
Social Networks, Algebra of
The Measures of Rank or Status: A Reformulation and Reinterpretation
This article investigates methods in social network analysis to identify the most important or the most prominent actors in a social network by ranking them appropriately. Although much has been done since Seeley's (Citation1949) seminal work, several questions remain: How does scaling an adjacency matrix of a social network affect its eigenvalues and their corresponding eigenvectors? How can the differences between the left and the right eigenve…
Determining groups from the clique structure in large social networks
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Determining groups from the clique structure in large social networks
The Measures of Rank or Status: A Reformulation and Reinterpretation
This article investigates methods in social network analysis to identify the most important or the most prominent actors in a social network by ranking them appropriately. Although much has been done since Seeley's (Citation1949) seminal work, several questions remain: How does scaling an adjacency matrix of a social network affect its eigenvalues and their corresponding eigenvectors? How can the differences between the left and the right eigenve…
Social Networks, Algebra of
Embedding time in positions: Temporal measures of centrality for social network analysis
Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra…
Exploring the effect of streamed social media data variations on social network analysis
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Computer Science (6 works) · Complex Network Analysis Techniques (5 works) · Opinion Dynamics and Social Influence (5 works) · Mathematics (4 works) · Artificial Intelligence (3 works) · Social media (3 works) · Social network analysis (3 works) · Sociology (3 works) · Theoretical Computer Science (3 works) · Combinatorics (2 works)