Rebuilding Institutional Legitimacy in Post-Conflict Societies: An Asia-Pacific Case Study, Interphase 1-2

Abstract

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

Career development in higher education through group mentoring: A case study of desirable attributes and perceptions of a current programme

“…Leximancer identifies core concepts within the data and illustrates how they are related (Leximancer Manual 2005); Leximancer is increasingly being used as a data analysis tool for qualitative data. It identifies themes or concept groups in text data, representing the clustering of key words (Fisk, Cherney, Hornsey, & Smith, 2009). 'The output produced by Leximancer provides a visual representation of these concepts and relationships and a means of quantifying and displaying the conceptual structure of a set of documents' (Fisk et al, 2009).…”

“…It identifies themes or concept groups in text data, representing the clustering of key words (Fisk, Cherney, Hornsey, & Smith, 2009). 'The output produced by Leximancer provides a visual representation of these concepts and relationships and a means of quantifying and displaying the conceptual structure of a set of documents' (Fisk et al, 2009). This method of combining the concept analysis tool Leximancer and thematic analysis has been utilised by researchers in the past (Galea & Loosemore, 2006) to provide a rich understanding of the data and to ensure no aspects are missed in the analysis stage.…”

Using online data and network-based text analysis in HRM research

“…Indeed, although network text analysis is particularly useful for analysing large volumes of text and we have discussed it here in connection with online textual data, it is important to note that it can be used for any type and volume of textual data. We illustrate the process using the Leximancer network text analysis software (Fisk et al, 2009;Smith and Humphreys, 2006), on a body of text that concerns the intersection of information technology and HRM, commonly referred to e-HRM in the literature (see e.g. Bondarouk et al, 2016).…”

Social Media Tools and Platforms in Learning Environments

“…Another feature of Leximancer is that 'it also allows the user to request overviews of text sources and key segments of texts in relation to specific concepts and relationships between concepts' (Fisk et al 2009). This feature was seen as a highly useful facet of the Leximancer data mining approach, as it helped single out text sources and key segments of texts in relation to specific concepts under discussion without needing to search through large samples of student blog and microblog text.…”