RECENS is a research center promoting high quality research in social network analysis, with an active participation in the Hungarian and international academic life. RECENS is part of the Centre for Social Sciences, HungarianAcademy of Sciences. It is situated in the beautiful Buda castle in Budapest, Hungary. For more information, please consult our website at recens.tk.mta.hu.
Graduates in any discipline with an interest in the study of social networks are encouraged to apply. Some background in network analysis is an asset. Ideal candidates received their MA/MSc degree between 2011 and 2013. Applicants with a scientific publication in hand and prize winners from student competitions (TDK, OTDK) will receive an advantage. Advanced skills in statistics and mathematics will be considered beneficial.
Besides working on the projects, the candidates have to attend weekly research meetings and seminars of RECENS and are expected to submit at least one article in an international peer-reviewed journal until the end of their second year and another paper until their third year.
The PhD students will receive scholarship for a three year period at the Doctoral School of Sociology at Corvinus University of Budapest, in which the graduates will work on an individual project, leading to a doctoral dissertation in English. RECENS offers to its own members PhD supervision, a supportive and cozy working climate, research collaboration at the national and international level, further trainings in methodology, office space, support for applications for further funding, and covers costs related to the research.
How to apply
The application procedure is organized by the Doctoral School of Sociology at Corvinus University of Budapest, so please mark in your application papers the intention to apply for one of the proposed positions and send a copy of your application material to recens@tk.mta.hu. Selection by the Doctoral School is a pre-requisite for working on these projects, but a further selection by the project initiators might be necessary.
For further information about the general application procedure, please consult szilvia.narai@uni-corvinus.hu.
Application material should be sent to
Szilvia Csehné Nárai
Corvinus University of Budapest
Fővám tér 8. II. floor, room 202.
1093 Budapest, Hungary.
For more information, please, visit our website at recens.tka.mta.hu or send us an mail to: recens@tk.mta.hu.
Proposed research topics:
- I. The Structure of Power Struggle in the Rákosi Era in a Network Perspective
History teaches us that the struggle for power at the top of the society can be very cruel. Cruelty and killing of rivals is often the rule rather than the exception in intense political power struggle where the winner takes everything: typically, a rule of a life-time. Strikingly, such examples are not peculiarities of the distant past.
We opt for a case study of dictatorship rather than a democracy because of the intensity of competition and because of a simpler analytical strategy: voters play a negligible role. We study the quest for power from 1949 till 1956 inHungary from a network perspective. We describe the dynamics of political relations and power in this period and illustrate whether our theoretical claims about negative relations and competition are valid in this social setting. For this purpose, we collect data about negativity and competition among politicians in Hungary from the time of communist dictatorship.
Our analytical strategy will include a decision about the target population; a selection of sources of relational information; definition of power positions; and operationalization and recording of relational aggression between politicians. For each step of the analytical strategy, independent assistance will be used for coding and processing data. Information obtained in each step will be checked in expert interviews. For the target population, we restrict our interest with a position generator method that is typical in the sociological research on the elite. Curricular data will be gathered about politicians who hold a position with significant power any time between 1949 and 1956 inHungary. This list will be supplemented with politicians who did not hold office, but were identified as key political actors in expert interviews with historians.
We analyze CVs and determine co-occurrences before 1956. Most typical early co-occurrences are communist activity in 1919 in Hungary, participation in the Soviet Red Army, imprisonment in Hungary (if in the same prison), strike activity in Hungary (especially in the construction industry), membership in the illegal communist party, emigration time in the Soviet Union (or elsewhere), representation at the Comintern, participation in the Spanish Civil War, partisan activity in World War II in Yugoslavia, in Hungary, or in the Soviet Union, membership in the Hungarian Front. More detailed CV information will be gathered for the period between 1945 and 1956. Some of these co-occurrences are co-incidental, but we will use them as relational indicators. That is, they partly measure potential friendship and alliance, and partly the effect of common background. In addition, to fill in missing gaps and to gain more insight, we code all positive and negative relational information from memoires and books written by historians. In addition, we record directed criticism in documented speeches, self-criticism that is triggered by another politician (“I was wrong… as it has been justly highlighted by Comrade X”), and direct involvement in arrests and political trials.
Recommended readings:
Fejtő F. 1991. A népi demokráciák története. (Histoire des démocraties populaires.) Ford. Endreffy Z. 1991. Budapest, Párizs, Magvető - Magyar Füzetek, 1. köt.
Izsák L. 1995. A Rákosi-rendszer. 1948 ősze-1956 nyara. Történelmi Szemle, 1:51-67.
Korom M. 1998. A hatalomgyakorlás "stabilitása." Államvédelmi Bizottság Magyarországon, 1948-1953. Új Horizont, 5-6:62-77.
Pünkösti Á. 1996. Rákosi a csúcson, 1948–1953. Budapest, Európa.
For this project, the applicant should be fluent in Hungarian. The candidate will need tocollect data and perform the analysis. The ideal candidate has experience in gathering archival information and has also a background in quantitative research methods and is recently graduated in history or in one of the social sciences.
II. Peer influence and academic performance among primary school pupils
In schools, negative relations related to status competition are largely responsible for situations in which low performance is enforced. If general norms support high efforts, a dense group without major division lines ostracizes those who do not comply. Negativity that is manifested as punishment of low performers has a positive impact on performance. A more disturbing example is when intensified competition leads to social exclusion of the best performing students and paradoxically lowers overall performance. In certain classrooms, similar to workplace environments, status can be attained by low performance and by advocating norms of performance lowering. If the large majority supports medium or low effort work, then best performers are likely to be punished and will be subjects of punishment. Strikingly, social exclusion of best performers is observable also in the best schools. In the latter case, if academic standards are shifted upwards, then social exclusion of best performers (geeks) could paradoxically be more likely. If standards of evaluation are linked to past performance, high performance poses a threat to the entire group, hardening to achieve the same grades due to higher standards.
Moreover, status orders do not necessarily reflect on academic achievement. Among others, status could be based on attractiveness, wealth, and sociability. If high status individuals tend to be low-performers, status competition could reward norms of low performance. Furthermore, stable sub-groups can maintain inefficient norms that limit achievement despite the presence of another sub-group in which achievement is approved. Therefore, it is of high importance which network topologies can contribute best to higher performance. We will analyze these structural conditions considering negative and positive relations in the school context.
Recommended readings:
Altermatt, E. R., & Pomerantz, E. M. (2005). The Implications of Having High-achieving versus Low-achieving Friends: A Longitudinal Analysis. Social Development, 14(1), 61-81
Davies, M., & Kandel, D. B. (1981). Parental and Peer Influences on Adolescents’ Educational Plans: Some Further Evidence. American Journal of Sociology 87 (2): 363-387.
Flashman, J. (2012). Academic Achievement and Its Impact on Friend Dynamics. Sociology of Education, 85(1), 61-80.
The candidate should participate in registering and analyzing our network panel data in Hungarian primary school classes. The ideal candidate has good skills in advanced statistics and at least a basic knowledge of social network analysis.
III. Longitudinal analysis of status competition and social exclusion in primary school classes
School classes are quite closed communities with fixed boundaries. Norms and behavior are under development, and therefore interventions and prevention programs could be designed and implemented more successfully than later in the life course. Besides, network ties and status orders change more rapidly at this age than in adulthood. In school classes, we have good chances to capture the whole network and the entire scope of status dimensions, which is burdensome in other empirical settings.
Status competition among pre-adolescents is relatively intense. It is not uncommon to see huge investments in strategic activities such as gossip, mediation, intervention, relational aggression, and sanctions on others for the sake of popularity and status. If everyone does so, we can observe a social dilemma situation: efforts invested are only sufficient to maintain or slightly modify the existing status order.
We try to examine which actors use relational aggression to strengthen their status positions and how this contributes to social exclusion. We are going to test competing predictions derived by using exponential random graph models (ERGMs), in particular p* and R-SIENA models that allow us to control for social background and variable attributes and for the separation of selection and influence effects.
Recommended readings:
Faris, Robert and Ennett, Susan (2010): Adolescent aggression: The role of peer group status motives, peer aggression, and group characteristics. Social Networks, forthcoming. doi:10.1016/j.socnet.2010.06.003
Faris, Robert and Felmlee, Diane (2011): Status Struggles: Network Centrality and Segregation in Same- and Cross-Gender Aggression. American Sociological Review, 76: 48-73.
Light, J.M. & Dishion, T. J. (2007). Early Adolescent Antisocial Behavior and Peer Rejection: A Dynamic test of a developmental process. New Directions for Child and Adolescent Development, 118, 77-89.
The candidate should participate in registering and analyzing our network panel data in Hungarian primary school classes. The ideal candidate has good skills in advanced statistics and at least a basic knowledge of social network analysis.
IV. Structural balance and ethnic segregation in school classes
School classes in primary schools are not homogenous, and are typically fractured along salient demographic characteristics, gender and ethnicity in particular. Even in integrated schools, friendship ties are highly segregated. Segregation of friendship ties could correlate with the emergence of subcultures that may oppose the objectives of schools and the educational system. If friendship ties remain segregated in integrated classrooms, disadvantaged pupils will be not influenced by mainstream role models, and integrated education may reduce differences in scholastic performance to a lesser extent than desired.
Friendship segregation can arrive at an unexpectedly high level due to a self-reinforcing cascade: we claim that few initial negative ties between members of different ethnic groups are sufficient to induce a balancing mechanism, in which positive ties will bind in-group members together and negativity will be the characteristic of out-group relations.
Status competition intensifies segregation as in-group members actively disapprove out-group members to strengthen their in-group ranks. A worst case scenario is when in-group members disapprove also the underlying norms of the out-group. The out-group can also be labeled to have completely opposite norms, in particular, with regard to school performance. Societal status relations contribute to determine which labels will be used by which ethnic group at the outset. In a self-reinforcing dynamics, members of the disadvantaged group will even enforce their members to an anti-school platform. In this subproject, we refine and test these hypotheses.
Furthermore, intergroup rivalry at the societal level could make dyadic relationships also painful and tense in the classroom. Even in less turbulent times, status differences between the groups could legitimize dyadic asymmetry and aggressive acts towards members of the lower status group. When relational aggression of this kind takes place to a remarkable extent, then intergroup status inequality is reinforced and could even grow. In a segregated social network full of ethnic tension, a viscous cycle might occur and larger status differences could potentially be observed than otherwise.
Recommended readings:
Baerveldt, C., Van Duijn, M.A.J., Vermeij, L., & D. A. van Hemert (2004). Ethnic boundaries and personal choice. Assessing the influence of individual inclinations to choose intra-ethnic relationships on pupils' networks. Social Networks 26(1), 55-74.
Downey, D. B. (2008). Black/White differences in School Performance: The Oppositional Culture Explanation. Annual Review of Sociology, 34 (42), 107-126.
Moody, J. (2001): Race, School Integration, and Friendship Segregation in America. American Journal of Sociology, 107(3): 679-716.
The candidate should participate in registering and analyzing our network panel data in Hungarian primary school classes. The ideal candidate has good skills in advanced statistics and at least a basic knowledge of social network analysis.
V. Network dynamics of rivalry and partnerships among firms
Market competition, but also market alliances are studied extensively by economists. Within the scope of economics, however, there are fewer studies about practices that are very often side-products of competition: reputation worsening, deception, fraud, purposeful price attacks, or law suits. Managers can affirm that the relationship between market competitors, but also allies can become loaded with negative emotions which sometimes result in revenge for previous unfavorable events. These back-door practices are especially given room in poorly regulated and less institutionalized markets. In these markets, organizations have more freedom to act deceitfully or take revengeful actions.
In this research project, we aim to explore in one well defined market environment the structure and dynamics of observed negative relations through a time span of a couple of years. We construct a data set about negative and positive dyadic relationships. We connect relational information with indicators of market success (market revenue, profit, market share) and test our theoretical predictions about how they are interrelated.
Unfortunately, the most poorly regulated segments with strong competition, in which most of negative practices can be expected, are also the ones, in which it is most difficult to gather objective information on negative relations, such as delayed payment, unpaid bills, and deceitful strategies. Although manager interviews could highlight most of the unfavorable events suffered, but they would be unable to provide an objective view on business relationship histories.
Therefore, we decide to collect data retrospectively from secondary sources that are easily tractable, such as filed complaints and commercial court cases (including the most severe cases of asking for bankruptcy) in a market segment with strong competition. Our selection criteria will be based on expected density of negative ties, data availability, and easily identifiable market segment boundaries and players. For any market segment, the boundary specification will already be much more difficult than in most other social settings. Market niches between competitors are just partly overlapping. Small and larger producers could supply to different retailers. There might be strong regional dependency. There might be new entrants and mergers. And many more factors could complicate our decision about the relevant firms included. We plan to overcome these problems by restricting our interest to a market with a relatively small number of competitors.
Recommended readings:
Beckman, Christine M.; Haunschild, Pamela R., and Phillips, Damon J. (2004): Friends or Strangers? Firm-Specific Uncertainty, Market Uncertainty, and Network Partner Selection. Organization Science, 15(3): 259-275.
Trapido, Denis (2012): Dual Signals. How Competition Makes and Breaks Interfirm Social Ties. Organization Science, 24(2): 498-512.
Uzzi, Brian (1997): Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42: 35-67.
Uzzi, Brian and Lancaster, Ryon (2004): "Embeddedness and Price Formation in the Corporate Law Market," American Sociological Review, 69: 319-344.
The candidate should gather and analyze data on network relations between firms. The ideal candidate has good organization skills and is capable of conducting advanced statistics and has at least a basic knowledge of social network analysis.