Combining data and text mining techniques for analysing financial reports

There is a vast amount of financial information on companies' financial performance available to investors in electronic form today. While automatic analysis of financial figures is common, it has been difficult to extract meaning from the textual parts of financial reports automatically. The textual part of an annual report contains richer information than the financial ratios. In this paper, we combine data and text mining methods for analysing quantitative and qualitative data from financial reports, in order to see if the textual part of the report contains some indications about future financial performance. The quantitative analysis has been performed using self‐organizing maps, and the qualitative analysis using prototype‐matching text clustering. The analysis is performed on the quarterly reports of three leading companies in the telecommunications sector. Copyright © 2004 John Wiley & Sons, Ltd.     

Funding Pain: Bedouin Women and Political Economy in the Naqab/Negev

ABSTRACT

This contribution focuses on the experiences and voices of Palestinian Bedouin women surviving and challenging Israeli colonial policies while residing in their own land and, in particular, the Bedouin women of the Naqab living in unrecognized villages. Through interviews and focus groups, this study learns from and engages with the voices of Palestinian Bedouin women because colonized women's criticisms of the political economic apparatus are seldom invoked to influence policy. Exploring these women's voices offers an opportunity to examine the political economy of their unrecognized, officially nonexistent villages and homes and to rectify the gap in bottom-up knowledge of political economy by investigating the institutional structures that define and circumscribe women's lives. Privileging Bedouin women's production of knowledge carries the analytical value of studying political economy based on women's own experiences and struggles against hegemony.