Solidarity, the network and the history of workers' self-management from the Gdańsk Agreement to shock therapy

This PhD thesis is an empirical research project in the field of modern Polish history. The thesis focuses on Solidarity, the Network and the idea of workers’ self-management. In addition, the thesis is based on an in-depth analysis of Solidarity archival material. The Solidarity trade union was born in August 1980 after talks between the communist government and strike leaders at the Gdansk Lenin Shipyards. In 1981 a group called the Network rose up, due to cooperation between Poland’s great industrial factory plants. The Network grew out of Solidarity; it was made up of Solidarity activists, and the group acted as an economic partner to the union. The Network was the base of a grass-roots, nationwide workers’ self-management movement. Solidarity and the self-management movement were crushed by the imposition of Martial Law in December 1981. Solidarity revived itself immediately, and the union created an underground society. The Network also revived in the underground, and it continued to promote self-management activity where this was possible. When Solidarity regained its legal status in April 1989, workers’ self-management no longer had the same importance in the union. Solidarity’s new politico-economic strategy focused on free markets, foreign investment and privatization. This research project ends in July 1990, when the new Solidarity-backed government enacted a privatization law. The government decided to transform the property ownership structure through a centralized privatization process, which was a blow for supporters of workers’ self-management. This PhD thesis provides new insight into the evolution of the Solidarity union from 1980-1990 by analyzing the fate of workers’ self-management. This project also examines the role of the Network throughout the 1980s. There is analysis of the important link between workers’ self-management and the core ideas of Solidarity. In addition, the link between political and economic reform is an important theme in this research project. The Network was aware that authentic workers’ self-management required reforms to the authoritarian political system. Workers’ self-management competed against other politico-economic ideas during the 1980s in Poland. The outcome of this competition between different reform concepts has shaped modern-day Polish politics, economics and society.

Russian social networks on the web: cohesion and coherence in Vkontakte

In this thesis connections between messages on the public wall of the Russian social network Vkontakte are analysed and classified. A total of 1818 messages from three different Vkontakte groups were collected and analysed according to a new framework based on Halliday and Hasan’s (1976) research into cohesion and Simmons’s (1981) adaptation of their classification for Russian. The two categories of textuality, cohesion and coherence, describe the linguistic connections between messages. The main aim was to find out how far the traditional categories of cohesion are applicable to an online social network including written text as well as multimedia-files. In addition to linguistic cohesion the pragmatic and topic coherence between Vkontakte messages was also analysed. The analysis of pragmatic coherence classifies the messages with acts according to their pragmatic function in relation to surrounding messages. Topic coherence analyses the content of the messages, describes where a topic begins, changes or is abandoned. Linguistic cohesion, topic coherence and pragmatic coherence enable three different types of connections between messages and these together form a coherent communication on the message wall. The cohesion devices identified by Halliday and Hasan and Simmons were found to occur in these texts, but additional devices were also identified: these are multimodal, graphical and grammatical cohesion.

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.