misc

Advances in socio-semantic network analysis: discussion panels

Wed, 03 Jul 2019 11:18:36 +0100

In recent years, I have been a co-organizer for the organized session on Advances in socio-semantic network analysis at the Sunbelt conference. This session addresses an emerging framework, where semantic and social network data are being jointly appraise. Alongside presentations on work addressing theoretical, methodological and empirical work at the nexus of social and semantic networks, this session also created a space for discussion (panels) on a number of theoretical and methodological challenges this framework poses.

The discussion panels stimulated open discussion on relevant issues in socio-semantic network analysis and triggered engaging conversations on a number of topics. To summarize all of these engaging discussions and to keep the conversation going, I have created a Google Document (see also link below) containing information about the organized session, my co-organizers, the discussion topics, as well as a summary of the discussions. This document will be updated after each Sunbelt conference so please save this link or follow my blog for updates.

Link to the document:
https://docs.google.com/document/d/e/2PACX-1vQZw7WxzvvnG8LgS0Oa2A_d1I6Lx6YY2QH-zq3dfNyBQQns563iFEtwJ2vF6oEScsEDMLsxFTxdISGR/pub

HuC Live blog post on mixing methods for social media analysis

Mon, 07 Jan 2019 10:18:19 +0100

Refugee or Migrant? Mixing methods for social media analysis

Cross-institutional research interests

Thu, 30 Nov 2017 14:02:53 +0100

The network representation presented the overlap in research interests between researchers of multiple institutes, where the number of common research interests is represented by the width of the link. More details on this will follow.

Refugee, migrant, or asylum seeker crisis?

Mon, 27 Jun 2016 03:11:39 +0100

In recent years, the precarious and unstable situation in the Middle East has pushed many to flee their countries and seek refuge in neighboring countries and in Europe. In April 2015, when five boats sank in the Mediterranean Sea, killing more than 1,200 people, the phrases "European migrant crisis" and "European refugee crisis" became widely used by media and politicians alike. Such phrases, serve as frames that alter perceptions and perhaps even influence behaviors. While “refugee” portrays people fleeing armed conflict or persecution, “migrant” describes people who make a conscious choice to leave their country to seek a better life elsewhere. These dichotomized characterizations can have serious consequences for the lives and safety of asylum seekers, they can undermine public support, steer public opinion, and frame the debate on how the world should react to this crisis.

To be presented at NetGlow 2016

Framing and Blaming: Socio-Semantics of the Eurocrisis

Sat, 11 Jun 2016 12:05:57 +0100

In this paper, we analyze a combination of social and semantic networks extracted from news media articles on the recent European debt crisis. While most network research, so far, has focused on either social networks or semantic networks, we combine networks of entities (i.e., organizations and actors) and semantic networks to identify the discursive frames used to characterize these different entities. The use of socio-semantic networks in the analysis of discursive fames is a novel approach in network research.

Media reporting of the financial crisis in the United States has been widely investigated by communication researchers, but the same does not apply to the European debt crisis. Since the end of 2009, several Eurozone member states were unable to repay or refinance their government debt or to bailout over-indebted banks under their national supervision. Spillover effects of the financial situation in the United States and the rising sovereign debt of several Eurozone states contributed to high financial instability in Europe. In reporting these events of the Eurozone debt crisis, the media makes use of frames to make their reports more prominent and/or popularize the issues discusses. The importance of frames in media reports stems from their ability to highlight some aspects of a perceived reality and make them more salient, while at the same time hiding other aspects. By employing frames to characterize or describe the financial situation of the Eurozone, media reports have the potential to influence perceptions surrounding the crisis, to motivate action, or to potentially create panic among their audiences.

Using semantic network analysis, the structural space approach, and parts of speech tagging, we identify different types of frames on a monthly basis in 1105 news items published by The Financial Times between October 2009 and October 2010. We show the over time evolution of frames used by The Financial Times to characterize organizations and actors (i.e., entities) in the debate relevant to the financial crisis. Our results show that the debate was only framed as a ‘crisis’ from January 2010 onwards, and that the similarity of correlations between our semantic networks are in a large part driven by shared concepts, but they are also driven by the structure of these networks beyond the common nodes. This means that both the content and the structure of the frame networks changes during the crisis. Our work contributes to socio-semantic network analysis by revealing the context in which entities are framed and blamed in relation the Eurocrisis.
Presented at Sunbelt 2016

Shifting discourses of the European Central Bank and the Federal Reserve System: Exploring ...

Sat, 11 Jun 2016 11:45:32 +0100

Using semantic network analysis, we explore a combination of structural measures, the structural space method. This method proves valuable for a more comprehensive dynamic analysis of large formal discourse corpora. Formal discourse is characterized by repetitive, and perhaps uninformative top ranked concepts, which makes the more subtle dynamic discursive shifts difficult to recognize. Combining popularity and connectivity potential of concepts in semantic networks, we reveal important dynamic shifts in the discourses of the European Central Bank (ECB) and the Federal Reserve System (FED). Structurally different, the roles of the ECB and the FED and their main objectives are comparable. These organizations determine the monetary policy for large currency areas and use communications as policy instruments to influence financial market developments. Their roles and consequently their discourse become even more important in times of crisis when financial market uncertainties intensify. This prompts a close investigation of how the discursive practices of the ECB and the FED have been affected by the financial crisis. The press releases issued by the ECB and the FED have been aggregated into four sets of two years representing the pre-crisis period, the crisis period, the post-crisis period, and the recovery period. Our analysis shows crisis-oriented terminology emerging since the pre-crisis period in both discourses and that the post-crisis discourse of the ECB enters a ‘new’ state containing characteristics of both the pre-crisis and the crisis period. This state appears to be a transition in the ECB discourse towards a new state and not towards the status quo of the pre-crisis period. In the post-crisis period, the FED’s discourse exhibits a moderate reversion to the pre-crisis period but also a significant reversal of emphasis from the crisis period. The recovery period reveals both discourses departing further from the crisis discourse.
Presented at EUSN, Barcelona, 2014

Inter-university collaboration via co-authorsip

Fri, 22 Apr 2016 10:48:55 +0100

A small project I am working on that is looking at co-autorships among scientists from different universities within the same scientific field. Because the data is under embargo, more details will follow. The structure of the network below is very interesting though!

The decline of semantic network analysis?

Fri, 11 Mar 2016 11:11:35 +0100

An interesting graph generated via Google Books Ngram Viewer for some of the key terms related to my area of expertise: